Driver Profiles Based Upon Driving Behavior With Passengers

ABSTRACT

In a computer-implemented method for detecting and acting upon driver behavior while driving with passengers, telematics data is collected by one or more electronic subsystems of a vehicle and/or mobile electronic device of a driver or passenger. The collected data is transmitted to a computer system, and analyzed to identify respective time periods during which the driver of the vehicle drove with and without passengers, and one or more driving behaviors of the driver during those time periods. The method also includes determining, based upon the driving behavior(s) of the driver during the time periods with and without passengers, how the driver modifies his or her driving when driving with or without passengers, and conveying to an entity at least a portion of a driver profile associated with the driver that has been adjusted based upon how the driver modifies his or her driving.

CROSS REFERENCE TO RELATED APPLICATIONS

This is a continuation of U.S. Pat. Application No. 16/919,596, filed onJul. 2, 2020 and entitled “Driver Profiles Based Upon Driving BehaviorWith Passengers,” which is a continuation of U.S. Pat. Application No.15/784,822, filed on Oct. 16, 2017 and entitled “Driver Profiles BasedUpon Driving Behavior With Passengers,” which claims the benefit of U.S.Pat. Application No. 62/414,291, filed on Oct. 28, 2016 and entitled“Systems and Methods for Generating and Using Driver Profiles,” and ofU.S. Pat. Application No. 62/524,208, filed on Jun. 23, 2017 andentitled “Driver Profiles Based Upon Driving Behavior With Passengers.”The disclosure of each of the above-identified patent applications ishereby incorporated herein by reference in its entirety.

FIELD OF THE DISCLOSURE

The present application relates generally to vehicle telematics and,more specifically, to technologies for generating, updating, and/orusing driver profiles based upon vehicle telematics and/or other data.

BACKGROUND

The technical field of vehicle telematics has advanced rapidly in recentyears, making it possible to learn far more information about driverhabits and behaviors than was previously possible. For example, existingtechnologies may collect and analyze data indicative of a driver’sacceleration, braking and cornering habits. By analyzing such data, someof these existing technologies are configured to generate/output datathat may be used to assess driver performance and driver risk. However,existing telematics-based technologies fail to leverage various kinds ofinformation that may be highly probative of a driver’s characteristicsor qualities, and/or fail to recognize numerous applications in whichsuch information may provide benefits.

BRIEF SUMMARY

In one aspect, a computer-implemented method for detecting and actingupon driver behavior while driving with passengers includes: (1)collecting telematics data by one or both of (i) one or more electronicsubsystems located on or in a vehicle and (ii) a mobile electronicdevice of a driver or a passenger in the vehicle, wherein collecting thetelematics data includes collecting exterior sensor data by one or moresensors indicative of an environment external to the vehicle; (2)transmitting, by the one or more electronic subsystems or by the mobileelectronic device, the telematics data to a computer system; (3)identifying, by analyzing the collected telematics data with one or moreprocessors of the computer system, (i) one or more time periods duringwhich the driver drove with one or more passengers, (ii) one or moreother time periods during which the driver drove without passengers,(iii) one or more driving behaviors of the driver during the one or moretime periods, and (iv) one or more driving behaviors of the driverduring the one or more other time periods; (4) determining, by one ormore processors of the computer system and based upon (i) the one ormore driving behaviors of the driver during the one or more time periodsand (ii) the one or more driving behaviors of the driver during the oneor more other time periods, how the driver modifies his or her drivingwhen driving with passengers as compared to when driving alone; and/or(5) conveying to an entity, by the one or more processors of thecomputer system via a network, at least a portion of a driver profileassociated with the driver that has been adjusted based upon how thedriver modifies his or her driving.

In another aspect, a system for detecting and acting upon driverbehavior while driving with passengers includes a device or subsystemthat includes one or both of (i) one or more electronic subsystemslocated on or in a vehicle, and (ii) a mobile electronic device of adriver or a passenger of the vehicle, and is configured to: (1) collecttelematics data, including external sensor data that is generated by oneor more sensors and indicative of an environment external to thevehicle; and (2) transmit the telematics data to a computer system. Thesystem also includes the computer system, which includes one or moreprocessors and a memory. The memory stores instructions that, whenexecuted by the one or more processors, cause the computer system to:(1) identify, by analyzing the collected telematics data, (i) one ormore time periods during which the driver of the vehicle drove with oneor more passengers, (ii) one or more other time periods during which thedriver drove without passengers, (iii) one or more driving behaviors ofthe driver during the one or more time periods, and (iv) one or moredriving behaviors of the driver during the one or more other timeperiods; (2) determine, based upon (i) the one or more driving behaviorsof the driver during the one or more time periods and (ii) the one ormore driving behaviors of the driver during the one or more other timeperiods, how the driver modifies his or her driving when driving withpassengers as compared to when driving alone; and (3) convey to anentity, via a network, at least a portion of a driver profile associatedwith the driver that has been adjusted based upon how the drivermodifies his or her driving.

Advantages will become more apparent to those skilled in the art fromthe following description of the preferred embodiments which have beenshown and described by way of illustration. As will be realized, thepresent embodiments may be capable of other and different embodiments,and their details are capable of modification in various respects.Accordingly, the drawings and description are to be regarded asillustrative in nature and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an exemplary computer system forgenerating, modifying, and/or using driver profiles;

FIG. 2 depicts exemplary data categories that may be utilized by thecomputer system of FIG. 1 to generate or modify a driver profile;

FIG. 3 depicts exemplary profile information categories that may bedetermined by the computer system of FIG. 1 when generating or modifyinga driver profile;

FIG. 4 depicts an exemplary mapping of a driver profile to criteriaassociated with particular vehicles;

FIG. 5 depicts an exemplary mapping of a driver profile to criteriaassociated with particular vehicle components;

FIG. 6 is a flow diagram of an exemplary computer-implemented method fordetecting and acting upon driver responsiveness to vehicle alerts;

FIG. 7 is a flow diagram of an exemplary computer-implemented method fordetecting and acting upon driver compliance with driver-specificlimitations;

FIG. 8 is a flow diagram of an exemplary computer-implemented method fordetecting and acting upon driver behavior while driving with passengers;

FIG. 9 is a flow diagram of an exemplary computer-implemented method foridentifying a suggested vehicle for a driver;

FIG. 10 is a flow diagram of an exemplary computer-implemented methodfor identifying a suggested vehicle component for a driver; and

FIG. 11 is a block diagram of an exemplary computer system on which oneor more of the embodiments described herein may be implemented.

The Figures depict aspects of the present invention for purposes ofillustration only. One skilled in the art will readily recognize fromthe following discussion that alternate aspects of the structures andmethods illustrated herein may be employed without departing from theprinciples of the invention described herein.

DETAILED DESCRIPTION

The embodiments described herein relate to, inter alia, systems andtechniques for generating, modifying, and/or using profiles fordrivers/operators of vehicles. The driver profile may be generatedand/or modified using vehicle telematics data indicative of how theoperator drives the vehicle (e.g., acceleration data, braking data,etc.), data indicative of when and/or where the operator drives thevehicle (e.g., GPS data), data indicative of the circumstances in whichthe operator drives the vehicle (e.g., camera or other sensor dataindicating the presence of passengers in the vehicle, the distancebetween the driver’s vehicle and other vehicles, weather, etc.), and/orother data (e.g., demographic information, dealership informationregarding recalls or maintenance, etc.).

As the term is used herein, “vehicle telematics data” may include anysuitable type or types of data provided by the vehicle (e.g., one ormore sensors and/or subsystems of the vehicle), by a mobile electronicdevice carried within the vehicle (e.g., a smartphone or wearableelectronic device of the driver), and/or by any other electronic deviceor component carried on or within the vehicle. Depending upon thecontext and the embodiment, for example, vehicle telematics data mayinclude acceleration data generated by an electronic control system ofthe vehicle and/or by an accelerometer of the driver’s mobile electronicdevice, GPS data provided by a GPS unit of the vehicle and/or a GPS unitof the mobile electronic device, image or video data generated by acamera of the vehicle and/or a camera of the mobile electronic device,and so on.

In various different embodiments, the driver profiles may be used indifferent situations or scenarios. For example, the profiles may be usedto adjust insurance ratings (e.g., during initial underwriting, or whenrenewing a policy, etc.), to rate or showcase a driving instructor orstudent, to determine whether to provide a discount, and/or for otherpurposes. In some embodiments, the profile may include a rating that isindicative of the driver’s personal responsibility or trustworthiness,and may be used in situations where such qualities are of particularimportance. For example, responsibility ratings in driver profiles maybe used to adjust driver credit ratings (e.g., when applying for a loanor credit line), to determine whether an “IOU” may be accepted from anindividual, to determine whether candidates will be offered particularjobs, and so on.

I. Exemplary Computer System for Generating, Modifying, and/or UsingDriver Profiles

FIG. 1 is a block diagram of an exemplary system 10 for generating,modifying, and/or using driver profiles. The system 10 may include avehicle 12 having an on-board system 14, as well as a computer system16, a third party server 18, and a network 20. While FIG. 1 depictsvehicle 12 as an automobile, vehicle 12 may instead be a truck,motorcycle, or any other type of land-based vehicle capable of carryingat least one human passenger (including the driver).

Network 20 may be a single wireless network, or may include multiplecooperating and/or independent networks of one or more types (e.g., acellular telephone network, a wireless local area network (WLAN), theInternet, etc.). On-board system 14 and third party server 18 may bothbe in communication with the computer system 16 via network 20. WhileFIG. 1 shows only a single vehicle 12 and a single third party server18, it is understood that computer system 16 may communicate (e.g., vianetwork 20) with any number of different vehicles (e.g., one or moreother vehicles similar to vehicle 12, with on-board systems similar toon-board system 14) and/or any number of different third party servers.

Third party server 18 may be a server of an entity that is notaffiliated with either the driver of vehicle 12 or the entity owning,maintaining, and/or using computer system 16, and may be remote fromcomputer system 16 and/or vehicle 12. For example, in various differentembodiments discussed further below, third party server 18 may be aserver associated with a provider of a mapping service, a provider of aweather information service, an auto repair shop, an auto maker, an autodealership, an auto parts supplier, an entity that determines creditscores, and so on. As used herein, the term “server” may refer to asingle server, or multiple servers working in concert.

On-board system 14 may include a first external sensor 30 and a secondexternal sensor 32, each being configured to sense an environmentexternal to vehicle 12 (i.e., to sense physical characteristics of theenvironment external to vehicle 12), such as a still image or videocamera device, a lidar (laser remote sensing, or light detection andranging) device, a radar device, or a sonar device, for example. Each ofthe external sensors 30, 32 may be located on or inside vehicle 12. Forexample, one or both of the external sensors 30, 32 may be permanentlyaffixed to vehicle 12 (e.g., on the exterior or interior of the frame,on the dashboard, on the inner or outer surface of a windshield, etc.),or may be temporarily affixed to, or simply placed on or in, someportion of the vehicle 12 (e.g., placed on top of the dashboard, or in adevice holder affixed to the windshield, etc.).

External sensor 30 and/or external sensor 32 may be included in ageneral purpose computing device (e.g., as a software application andassociated hardware of a smartphone or other portable computer device),or may be a dedicated sensor device. In the example system 10 shown inFIG. 1 , external sensor 30 is located on or inside vehicle 12 such thatit senses the environment in a forward-facing range 34, while externalsensor 32 is located on or inside vehicle 32 such that it senses theenvironment in a rear-facing range 36. In some embodiments, the externalsensor 30 and external sensor 32 may combine to provide a 360 degreesensing range. In other embodiments, however, the external sensor 30 andexternal sensor 32 may be redundant sensors (of the same type, or ofdifferent type) that each provide a 360 degree sensing range. In stillother embodiments, external sensor 32 may be omitted, or the on-boardsystem 14 may include more than two external sensors.

Each of external sensors 30, 32 may generate data, or analoginformation, that is indicative of the sensed external environment. Inan embodiment where external sensor 30 is a digital video camera device,for example, external sensor 30 may generate data corresponding toframes of captured digital video. As another example, in an embodimentwhere external sensor 30 is a digital lidar device, external sensor 30may generate data corresponding to frames of captured digital lidarinformation.

On-board system 14 may also include one or more internal sensors 38. Insome embodiments, internal sensor(s) 38 may include one or more sensorsdesigned to detect the presence of passengers. For example, internalsensor(s) 38 may include inward-facing digital cameras arranged tocapture at least a portion of an interior (cabin) of vehicle 12, and/orone or more seat sensors configured to detect the presence of the driverand/or passengers in the respective seat(s). As another example,internals sensor(s) 14 may instead (or also) include seatbelt sensorsthat are configured to detect when each seatbelt in vehicle 12 isengaged or not engaged. In embodiments where internal sensor(s) 38include an inward-facing camera, the camera may be permanently affixedto vehicle 12 (e.g., on the interior of the frame, on the dashboard, onthe inner surface of a windshield, etc.), or may be temporarily affixedto, or simply placed on or in, some portion of the vehicle 12 (e.g.,placed on top of the dashboard, or in a device holder affixed to thewindshield, etc.). Moreover, a camera of internal sensor(s) 38 may beincluded in a general purpose computing device (e.g., as a softwareapplication and associated hardware of a smartphone or other portablecomputer device), or may be a dedicated sensor device.

On-board system 14 may also include hardware, firmware and/or softwaresubsystems that monitor and/or control various operational parameters ofvehicle 12. As seen in FIG. 1 , a braking subsystem 40 may generate dataindicative of how the brakes of vehicle 12 are applied (e.g., anabsolute or relative measure of applied braking force, or a binaryindicator of whether the brakes are being applied at all, etc.), a speedsubsystem 42 may generate data indicative of how fast the vehicle 12 isbeing driven (e.g., corresponding to a speedometer reading, anaccelerometer measurement, and/or a driver input such as depression of agas pedal, etc.), and a steering subsystem 44 may generate dataindicative of how the vehicle 12 is being steered (e.g., based upon thedriver’s manipulation of a steering wheel, or based upon automatedsteering control data, etc.).

A diagnostics subsystem 46 may generate other information pertaining tothe operation of vehicle 12, such as warning/alert information toindicate that one or more components of vehicle 12 is/are in need ofreplacement, an upgrade, and/or servicing. For example, diagnosticssubsystem 46 may generate an alert when tire pressure is low (e.g.,based upon a signal from a tire pressure sensor not shown in FIG. 1 ),when the engine is overheating (e.g., based upon a temperature sensor inthe engine compartment, also not shown in FIG. 1 ), when an oil changeis recommended, and so on.

The example system 10 may also include a Global Positioning Satellite(GPS) subsystem 48 that generates data indicative of a current locationof vehicle 12. In other embodiments, the subsystem 48 uses otherpositioning techniques instead of GPS, such as cell tower triangulation,for example.

In some embodiments, the braking subsystem 40, speed subsystem 42,steering subsystem 44, diagnostics subsystem 46, and/or one or moredifferent subsystems not shown in FIG. 1 may also generate dataindicating whether one or more automated driving systems (e.g., anadvanced driver assistance system (ADAS)) is/are currently activated forvehicle 12. For example, the speed subsystem 42 may generate dataindicating whether a conventional cruise control system is currentlyactivated, and/or the braking subsystem 40 or steering subsystem 44 maygenerate data indicating whether assisted steering and/or assistedbraking systems are currently activated. As other examples, a unit ofon-board system 14 (e.g., diagnostics subsystem 46, or another unit notshown in FIG. 1 ) may generate data indicating whether vehicle 12 is inan automated transmission mode or a manual transmission mode, or whetherthe driving of vehicle 12 is currently subject to completeautomated/machine control rather than manual (human) control, etc.

In some embodiments, the on-board system 14 may not include one or moreof the subsystems 40, 42, 44, 46, 48, one or both of external sensors 30and 32, and/or internal sensor(s) 38, and/or the on-board system 14 mayinclude additional devices or subsystems not shown in FIG. 1 . Moreover,one or more subsystems in on-board system 14 may be included in ageneral purpose computing device such as a smartphone. For example, theGPS subsystem 48 may include a software application running on asmartphone that includes the appropriate hardware (e.g., an antenna andreceiver).

On-board system 14 may also include a data collection unit 50 configuredto receive data and/or analog signals from external sensors 30, 32,internal sensor(s) 38, and/or some or all of subsystems 40, 42, 44, 46,48. The data collection unit 50 may collect the data and/or analogsignals substantially in real time, and in any of various differentways, according to different embodiments. In some embodiments, forexample, the data collection unit 50 may periodically sample data and/oranalog signals from the various external sensors 30, 32, internalsensor(s) 38, and/or subsystems 40, 42, 44, 46, 48, or be notified bythe respective sensors or subsystems when new data is available, etc.

In some embodiments, the data collection unit 50 may receive data fromone or more of the external sensors 30, 32, internal sensor(s) 38,and/or one or more of subsystems 40, 42, 44, 46, 48 via a wireless link,such as a Bluetooth link. Alternatively, one or more of subsystems 40,42, 44, 46, 48, internal sensor(s) 38, and/or external sensors 30 and/or32, may provide data to data collection unit 50 via messages placed on acontroller area network (CAN) bus (not shown in FIG. 1 ) or othersuitable bus type, and/or via an on-board diagnostics (OBD) system (alsonot shown in FIG. 1 ). For example, the data collection unit 50 maycollect information from diagnostics subsystem 46 (and/or from one ormore of subsystems 40, 42, 44) via one or more OBD ports. In someembodiments, the data collection unit 50 may collect data using a mix ofinterface and/or bus types (e.g., a Bluetooth interface to receive datafrom sensors 30, 32 and internal sensor(s) 38, an OBD port to receivedata from diagnostics subsystem 46, and a CAN bus to receive data fromsubsystems 40, 42, 44).

In some embodiments where one or more of external sensors 30, 32,internal sensor(s) 38, and/or one or more of subsystems 40, 42, 44, 46,48 generate analog signals, either the respective sensors/subsystems orthe data collection unit 50 may convert the analog information to adigital format. Moreover, the data collection unit 50 may convert datareceived from one or more of external sensors 30, 32, internal sensor(s)38, and/or one or more of subsystems 40, 42, 44, 46, 48, to differentdigital formats or protocols. After collecting (and possibly converting)the data from the various sensors/subsystems, the data collection unit50 may store the data in a memory 52. The memory 52 may be any suitabletype of data storage, such as a random access memory (RAM), a flashmemory, or a hard drive memory, for example.

On-board system 14 may also include a data processing unit 54 that iscoupled to the data collection unit 50. The data processing unit 54 mayinclude one or more processors, or represent software instructions thatare executed by one or more processors of on-board system 14, and may beconfigured to process the data collected by data collection unit 50 andstored in memory 52 for various purposes. In one embodiment, forexample, data processing unit 54 simply packages data collected by datacollection unit 50 into a format suitable for transmission to computingsystem 16. Alternatively, or in addition, data processing unit 54 mayanalyze the collected data to generate various types of information thatmay be used to update a driver profile, as discussed further below inconnection with computing system 16. Data processing unit 54 mayinclude, or be associated with, a memory 56 for storing outputs of thedata analysis and/or other processing. Memory 56 may be any suitabletype of data storage, such as a RAM, a flash memory, or a hard drivememory, for example. Memory 52 and memory 56 may be separate memories,or parts of a single memory, according to different embodiments.

Data processing unit 54 may be coupled to an interface 60, which maytransmit the data received from data processing unit 54 to computersystem 16 via network 20. Interface 60 may include a transmitter and oneor more antennas, for example. In an alternative embodiment, interface60 may instead be an interface to a portable memory device, such as aportable hard drive or flash memory device. In this embodiment, theportable memory device may be used to download data from memory 56 ofdata processing unit 54, and may be manually carried to computer system16 without utilizing network 20. In another alternative embodiment, aBluetooth or other short-range link may be used to download data frommemory 56 to a portable computer device (e.g., a laptop or smartphone),which may in turn be used to transmit the data to computer system 16 vianetwork 20. In some embodiments, interface 60 may represent multipletypes of different interfaces used for different types of data (e.g., aWLAN transceiver for data from external sensors 30, 32, a smartphonecellular transceiver for data from internal sensor(s) 38, and a flashmemory device port for data from subsystems 40, 42, 44, 46, 48).

In some embodiments, the data generated by data processing unit 54 andstored in memory 56 may be automatically sent to interface 60 fortransmission to computer system 16. For example, the data may be sent tointerface 60 at regular time intervals (e.g., once per day, once perhour, etc.). In other embodiments, the data may be sent to computersystem 16 in response to a query from computer system 16 that isreceived via network 20, or in any other suitable manner. Once the datais provided to computer system 16, the data may be subject to furtherprocessing (e.g., to generate or modify a profile for the driver ofvehicle 12), as discussed further below.

Computer system 16 may be an electronic processing system (e.g., aserver) capable of performing various functions, and may include aninterface 62 configured to receive data from on-board system 14 ofvehicle 12, and data from third party server 18, via network 20.Interface 62 may be similar to interface 60 of on-board system 14, forexample. In embodiments where a portable memory device (rather thannetwork 20) is used to transfer at least some of the data from on-boardsystem 14 to computer system 16, interface 62 may include an interfaceto a portable memory device, such as a portable hard drive or flashmemory device, for example.

Computer system 16 may also include a data collection unit 70 coupled tointerface 62. Data collection unit 70 may be configured toreceive/collect the data received by interface 62, and to store thecollected data in a memory 72. Memory 72 may be any suitable type ofdata storage, such as a RAM, a flash memory, or a hard drive memory, forexample. Data collection unit 70 may be coupled to a data analysis unit74. Data analysis unit 74 may include one or more processors, orrepresent software instructions that are executed by one or moreprocessors of computing system 16, and may be configured to process thedata collected by data collection unit 70 and stored in memory 72 forvarious purposes according to different embodiments, as discussedfurther below.

Generally, data analysis unit 74 may analyze data from vehicle 12 (e.g.,the data received from on-board system 14 via interface 60) and a numberof other vehicles to generate and/or modify/update driver profilesstored in a driver profiles database 76. In the example system 10 ofFIG. 1 , data analysis unit 74 includes a driving behavioridentification unit 80, a profile generation/update unit 82, a vehicleidentification unit 84, and a vehicle component identification unit 86.In other embodiments, data analysis unit 74 does not include one or moreof units 80, 82, 84, 86, and/or includes additional units not shown inFIG. 1 . For example, one or more of units 80, 82, 84, 86 may instead beimplemented by data processing unit 54 of on-board system 14 in vehicle12, or may be entirely absent from system 10. In one embodiment, each ofunits 80, 82, 84, 86 may include a set of instructions stored on atangible, non-transitory computer-readable medium and capable of beingexecuted by one or more processors of computer system 10 to perform thefunctions described below. In another embodiment, each of units 80, 82,84, and/or 86 includes a set of one or more processors configured toexecute instructions stored on a tangible, non-transitorycomputer-readable medium to perform the functions described below.

Driving behavior identification unit 80 may be generally configured toanalyze data received from vehicle 12 (e.g., from interface 60 ofon-board system 14, as discussed above) to detect and/or identifyvarious types of driving behaviors. For example, driving behavioridentification unit 80 may analyze data generated by subsystems 40, 42,and/or 44 to determine acceleration, braking, and/or cornering patternsof the driver of vehicle 12. As another example, driving behavioridentification unit 80 may analyze data generated by external sensor 34to determine an average (and/or a minimum, etc.) tailgating distancebetween vehicle 12 and other vehicles in front of vehicle 12, and/or todetermine proper/improper lane usage, etc. Other example drivingbehaviors that may be identified are discussed below in connection withFIG. 3 .

In some embodiments, each of one or more driving behaviors identified bydriving behavior identification unit 80 may be associated with tags orother metadata indicating the circumstances in which the drivingbehavior occurred. For example, driving behavior identification unit 80may determine a first set of acceleration, braking, and/or corneringpatterns and tag that set as being associated with times when the driverof vehicle 12 was accompanied by one or more passengers, and determine asecond set of acceleration, braking, and/or cornering patterns and tagthat set as being associated with times when the driver of vehicle 12was not accompanied by any passengers. Driving behavior identificationunit 80 may determine which sets correspond to the presence of one ormore passengers using data generated by internal sensor(s) 38, forexample.

As another example, driving behavior identification unit 80 maydetermine a first average tailgating distance and tag that distance asbeing associated with times when vehicle 12 was driven on wet or icyroads, determine a second average tailgating distance and tag thatdistance as being associated with times when vehicle 12 was driven onwet roads, and determine a third average tailgating distance and tagthat distance as being associated with times when vehicle 12 was drivenon dry roads. Driving behavior identification unit 80 may determinewhich distances correspond to the presence of icy, wet, or dry roadsusing data generated by external sensors 30 and/or 32, and/or data froma weather information service (e.g., in an embodiment where third partyserver 18 or another server not shown in FIG. 1 is associated with theweather information service), for example.

In alternative embodiments, data processing unit 54 may identify some orall of the driving behaviors. In such embodiments, driving behavioridentification unit 80 may be excluded from data analysis unit 74, ormay operate in conjunction with data processing unit 54. For example,data processing unit 54 may identify some types of driving behaviors,while driving behavior identification unit 80 identifies other types ofdriving behaviors and/or higher-level driving behaviors. In one suchembodiment, for instance, data processing unit 54 may determinetailgating distances to other vehicles using data from external sensor30 and image recognition algorithms (e.g., to identify an object aheadof vehicle 12 as another vehicle), and driving behavior identificationunit 80 may use that information, along with data from third partyserver 18 or another server, to determine an average tailgating distancefor each of a number of different weather conditions (e.g., sunny,partly cloudy, cloudy, fog, rain, snow, icy roads, etc.).

While not shown in FIG. 1 , data analysis unit 74 may also includeadditional units that determine behaviors not directly related to thedriver’s driving performance. For example, data analysis unit 74 mayalso include a unit that determines how and when a driver usesparticular features (e.g., cruise control, windshield wipers,headlights, etc.), and/or a unit that determines how responsive a driveris to alerts that are provided by on-board system 14, etc.

Profile generation/update unit 82 may be generally configured to use thedriving behaviors identified by driving behavior identification unit 80,and possibly also information identified by other units of data analysisunit 74 (e.g., feature usage patterns, etc.), to populate and/or updatefields of a driver profile for the driver of vehicle 12 in driverprofiles database 76. Each of a number of different drivers (includingthe driver of vehicle 12) may be associated with a different profile indriver profiles database 76, with each profile having one or more fieldsof information.

Each driver profile may, in some embodiments, include a “responsibilityrating” that indicates how responsible or trustworthy the driver may be(e.g., as determined based upon various driving behaviors and/or othertypes of information that are probative ofresponsibility/trustworthiness). In some embodiments, each profile alsoincludes a number of fields indicative of demographic and/or personalinformation (e.g., gender, age, education level, profession,disabilities/impairments/limitations, etc.), vehicle information (e.g.,vehicle model, year, and/or color), and/or other information. Driverprofiles database 76 may be stored in memory 72 or a similar memory, forexample, or may be external to computer system 16.

Vehicle identification unit 84 may be generally configured to identifyparticular vehicles that may be most appropriate for individuals basedupon the driving behaviors of those individuals, as identified bydriving behavior identification unit 80 and reflected in the driverprofile as generated or modified by profile generation/update unit 82.Vehicle identification unit 84 may also base the identification ofvehicles upon other information in the driver profile, such asdemographic information about each driver (e.g., age), each driver’sresponsibility rating, and/or other profile information. Some morespecific examples of the operation of vehicle identification unit 84 areprovided below in connection with FIG. 4 .

When vehicle identification unit 84 identifies one or more vehicles(e.g., vehicle makes, models, and/or years) that may be particularlywell-suited for an individual, computer system 16 may cause anindication of the identified vehicle(s) to be displayed to a user. Forexample, computer 16 may cause a monitor (not shown in FIG. 1 ) ofcomputer system 16 to display the indication within a user interfacepresented by a particular software application. As another example,computing device 16 may send data indicative of the identifiedvehicle(s) to a third party computing system (e.g., a computing systemof an auto dealership). As yet another example, computing device 16 maysend data indicative of the identified vehicle(s) to an email address(and/or telephone number for an SMS message) of the driver.

Vehicle component identification unit 86 may be generally configured toidentify particular vehicle components that may be most appropriate forindividuals based upon the driving behaviors of those individuals, asidentified by driving behavior identification unit 80 and reflected inthe driver profile as generated or modified by profile generation/updateunit 82. As used herein, the term “vehicle component” may refer to apart that is physically fixed to the vehicle, such as a tire or brakepad, or something that is not physically fixed to the vehicle but isused to facilitate vehicle operation, such as oil, brake fluid, or gas.Vehicle component identification unit 86 may also base theidentification of vehicle components upon other information in thedriver profile, such as demographic information about each driver (e.g.,age), each driver’s responsibility rating, etc. Some more specificexamples of the operation of vehicle component identification unit 86are provided below in connection with FIG. 5 .

When vehicle component identification unit 86 identifies one or morecomponents (e.g., by part number, or type and brand, etc.) that may beparticularly well-suited for an individual, computer system 16 may causean indication of the identified vehicle component(s) to be displayed toa user. For example, computer 16 may cause a monitor (not shown in FIG.1 ) of computer system 16 to display the indication within a userinterface presented by a particular software application. As anotherexample, computing device 16 may send data indicative of the identifiedvehicle component(s) to a third party computing system (e.g., acomputing system of an auto dealership). As yet another example,computing device 16 may send data indicative of the identifiedvehicle(s) to an email address (and/or telephone number for an SMSmessage) of the driver.

While FIG. 1 depicts an embodiment in which vehicle telematics data maybe generated and transmitted to computer 16 by an on-board system 14, inother embodiments some or all of the vehicle telematics data may insteadbe generated and/or transmitted to computer 16 by a mobile electronicdevice (e.g., a smartphone, a wearable electronic device, and/or anothermobile electronic device of the driver and/or a passenger of vehicle12). For example, an accelerometer, gyroscope, compass, and/or camera ofthe driver’s smartphone may be used to generate vehicle telematics data,which may be transmitted to computer 16 by either the smartphone itselfor on-board system 14 (e.g., after the smartphone transmits thetelematics data to on-board system 14 via a short-range communicationtechnology such as WiFi or Bluetooth). In embodiments where the driver’sor passenger’s mobile electronic device transmits some or all of thevehicle telematics data to computer 16, the mobile electronic device mayinclude an interface (e.g., similar to interface 60) that is configuredto transmit the data to computer 16 via network 20 or another network.

II. Exemplary Inputs for Generating or Modifying Driver Profiles

FIG. 2 depicts exemplary data categories 100 that may be utilized by thesystem 10 of FIG. 1 to generate or modify a driver profile, such as adriver profile included in driver profiles database 76 of computersystem 16. The data categories 100 may include operational data 102,sensor data 104, diagnostic data 106, location data 110, driver-provideddata 112, and/or third party data 114. In other embodiments, the datacategories 100 may include more, fewer, and/or different categories ofdata, and/or each category shown in FIG. 2 may include more, fewer,and/or different types of data.

Operational data 102 may include one or more types of data relating tooperation of a vehicle, such as speed data, acceleration data, brakingdata, cornering data, ADAS data (e.g., whether/when ADAS is engaged),drive mode data (e.g., data indicating whether the driver selected a“comfort,” “eco” or “sport” mode), headlight data (e.g., whether/whenheadlights are turned on), turn signal data (e.g., whether/when turnsignals are used), and/or windshield wiper data (e.g., whether/whenfront and/or rear wipers are used). Some or all of operational data 102may be data generated by subsystems 40, 42, 42, and/or 46 of FIG. 1 ,one or more other subsystems of vehicle 12 not shown in FIG. 1 , and/ora mobile electronic device of a driver or passenger.

Sensor data 104, which may overlap in definition with operational data102 to some degree, may include one or more types of data indicative ofinternal and external conditions of a vehicle, and particularlyconditions that may be captured by cameras, weight sensors, and/or othertypes of sensors. Sensor data 104 may include, for example, trafficcondition data, weather condition data, data indicating the number ofpassengers in the vehicle, data indicating when particular seatbelts areused, data indicative of tire pressure, and/or driver image data. Someor all of sensor data 102 may be data generated by external sensor 30,external sensor 32, and/or internal sensor(s) 38 of FIG. 1 , and/or by amobile electronic device of a driver or passenger. For example, externalsensor 30 and/or external sensor 32 may generate the traffic and/orweather data, internal sensor(s) 38 may generate the data indicative ofnumber of passengers, seatbelt usage data, and/or driver image data, anda different sensor of vehicle 12 (not shown in FIG. 1 ) may generate thetire pressure data.

Diagnostic data 106 may include one or more types of data indicative ofthe state of hardware and/or software systems of a vehicle, such as dataindicative of diagnostic fault codes, data indicative of safety warningsor alerts (e.g., a check engine alert, a low tire pressure warning, anoil change reminder, etc.), and/or data indicative of the currentversion of one or more units of software installed in the vehicle (e.g.,for on-board system 14 of FIG. 1 ). Some or all of diagnostic data 106may be data generated by diagnostic subsystem 46 of FIG. 1 , forexample.

Location data 110 may include one or more types of data indicative ofvehicle location. For example, location data 110 may include locationdata obtained from a GPS unit installed in a vehicle (e.g., GPSsubsystem 48 of FIG. 1 ), and/or location data obtained from a mobiledevice (e.g., smartphone, smart watch, etc.) of the driver that includesa GPS unit.

Driver-provided data 112 may include one or more types of dataindicative of a driver and his or her vehicle, such as driver age,driver gender, driver education level, driver profession, vehicle model,vehicle year, and/or vehicle color. As the label suggests,driver-provided data 112 may be data that the driver provided (e.g.,when filling out an application or other form or questionnaire).Alternatively, some or all of driver-provider data 112 may be obtainedin a different manner (e.g., provided by a third party, similar to thirdparty data 114).

Third party data 114 may include one or more types of data sourced byone or more third party entities. For example, third party data 114 mayinclude data indicative of specific driver limitations (e.g., visionimpairment, motor skill impairment, etc.), which may be obtained from agovernmental or other entity. As another example, third party data 114may include data indicative of speed limits, which may be obtained froma governmental entity, an entity that provides a mapping service, oranother entity. As yet another example, third party data 114 may includedata indicative of recall information (e.g., types and dates of recalls,dates of recall notices being sent, whether particular vehicles wereserviced to address a recall, etc.), which may be obtained from avehicle manufacturer or other entity. As still another example, thirdparty data 114 may include police blotter information (e.g., locationsand types of crimes and other offenses), which may be obtained from agovernmental or other entity.

As noted above, the data in the exemplary data categories 100 may beanalyzed by the system 10 of FIG. 1 to generate or modify a driverprofile, such as a driver profile included in driver profiles database76 of computer system 16. Various examples of how data shown in FIG. 2may be used to determine/set profile information are provided below inconnection with FIG. 3 .

III. Exemplary Information Determined for Driver Profiles

FIG. 3 depicts exemplary profile information categories 150 that may bedetermined by the system 10 of FIG. 1 (e.g., by data analysis unit 74)when generating or modifying a driver profile, such as a driver profileincluded in driver profiles database 76 of computer system 16. Theprofile information categories 150 may include driving behaviorinformation 152, feature usage information 154, alert responsivenessinformation 156, driver state information 158, and/or other information160. In other embodiments, the profile information categories 150 mayinclude more, fewer, and/or different categories than are shown in FIG.3 , and/or each category may include more, fewer, and/or different typesof information than are shown in FIG. 3 .

Driving behavior information 152 may include acceleration patterns,braking patterns, cornering patterns, compliance with speed limits,and/or compliance with driver limitations. For example, drivingbehaviors identification unit 80 or another unit of data analysis unit74 may determine acceleration, braking, and cornering patterns (e.g., anaverage and standard deviation of the time to accelerate from 0 to 30miles per hour, an average and standard deviation of the time to go from60 miles per hour to a complete stop, a metric relating speed to turnradius, and so on) using acceleration, braking, and cornering data fromoperational data 102 of FIG. 2 .

As another example, driving behaviors identification unit 80 or anotherunit of data analysis unit 74 may determine compliance with speed limits(e.g., a number of times in a particular time period that the postedspeed limit is exceeded by more than 5 miles per hour, a maximum amountor percentage by which a posted speed limit is exceeded in a particulartime period, etc.) using speed data from operational data 102 (or usingacceleration data of operational data 102 to determine speed), and speedlimit data from third party data 114, of FIG. 2 .

As yet another example, driving behaviors identification unit 80 oranother unit of data analysis unit 74 may determine compliance withdriver-specific limitations using one or more types of data withinoperational data 102 of FIG. 2 , one or more types of data within sensordata 104 of FIG. 2 , and driver limitation data from third party data114 of FIG. 2 . For example, driving behaviors identification unit 80 oranother unit of data analysis unit 74 may use data from external sensor30 and speed subsystem 42 of FIG. 1 to determine one or more metricsindicating how closely a driver follows other vehicles (“tailgates”) inrelation to his or her speed. Further, driving behaviors identificationunit 80 or another unit of data analysis unit 74 may determine from thethird party server 18 of FIG. 1 (e.g., a department of transportationwithin a state) or from the driver that he or she has a particular levelof vision impairment (e.g., shortsightedness or poor night vision),motor skill impairment (e.g., due to a handicap or injury), and/or othermedical conditions and/or physical characteristics that may limit how heor she can safely operate a vehicle. Thereafter, driving behaviorsidentification unit 80 may determine whether the driver tends to followother vehicles at a “safe” distance, in light of known correlationsbetween drivers with similar limitations and the occurrence ofaccidents. Other driving behaviors (e.g., braking patterns, corneringpatterns, windshield wiper usage, etc.) may also, or instead, beanalyzed in connection with any driver-specific limitations.

In some implementations, one or more of the types of information indriving behavior information 152 may be further subdivided based uponconditions at the time of the behavior. For example, some or all of thedriving behavior information 152 may be associated with differentweather conditions, different traffic conditions, different times and/orlighting conditions (e.g., day, evening, night, etc.), different vehiclemodels (e.g., if profile information is separately determined formultiple vehicles of a driver), different types of roads/areas, and soon. Thus, for instance, driving behavior information 152 may includecompliance with speed limits (e.g., an indication of how often and/orlong the driver exceeds the speed limit by a predetermined thresholdamount) for heavy traffic, and also compliance with speed limits forlight and/or moderate traffic. As another example, driving behaviorinformation 152 may include compliance with speed limits in schoolzones, as well as compliance with speed limits on interstate roads. Asyet another example, driving behavior information 152 may includeacceleration, braking, and cornering patterns in clear weather, as wellas similar patterns in rainy, foggy, and/or snowy/icy weather.

Feature usage information 154 may include seatbelt usage, weather-and/or time-of-day-specific headlight usage, weather-specific windshieldwiper usage, and/or traffic-dependent cruise control usage. For example,driving behaviors identification unit 80 or another unit of dataanalysis unit 74 may use seatbelt data from sensor data 104 of FIG. 2 todetermine how often a seatbelt is used for the driver (and/or one ormore passengers). As another example, driving behaviors identificationunit 80 or another unit of data analysis unit 74 may use headlight datafrom operational data 102 and weather condition data from sensor data104 and/or third party data 114 to determine how often (and/or for howlong) the driver uses vehicle headlights when driving at night, in foggyweather, and/or when raining.

As yet another example, driving behaviors identification unit 80 oranother unit of data analysis unit 74 may use windshield wiper data fromoperational data 102 and weather condition data from sensor data 104and/or third party data 114 to determine how often (and/or for how long)the driver uses windshield wipers when it is raining heavily and/orlightly. As still another example, driving behaviors identification unit80 or another unit of data analysis unit 74 may use ADAS or other datafrom operational data 102 and traffic condition data from sensor data104 and/or third party data 114 to determine how often (and/or for howlong) the driver uses cruise control in various different degrees oftraffic.

Alert responsiveness information 156 may include responsiveness tomalfunction/service indicators (e.g., a check engine light, a low tirepressure warning, an oil change reminder light, a faulty sensorindicator, etc.), responsiveness to maintenance dates (e.g., whether thedriver has his or her vehicle serviced partially or wholly in accordancewith maintenance recommendations, such as those in a user’s manual),and/or responsiveness to vehicle recall notices (e.g., for a defectiveair bag, etc.). For example, driving behaviors identification unit 80 oranother unit of data analysis unit 74 may determine an amount of timebetween a malfunction/service indicator being activated on a dashboardof vehicle 12 and the driver (or another individual) either correctingthe problem (e.g., by filling low tires with air) or having the vehicleserviced to correct the problem (e.g., taking the vehicle to a repairshop or dealer to address a check engine light issue).

The determination may be made using data such as diagnostic fault codeand/or safety warning data of diagnostic data 106 in FIG. 2 (e.g., todetermine when an alert was first triggered, and possibly also todetermine when the problem was resolved), and possibly data from a thirdparty such as data from third party server 18 of FIG. 1 (e.g., if thirdparty server 18 is associated with a dealer that services the vehicle),for example. Driving behaviors identification unit 80 or another unit ofdata analysis unit 74 may also determine other information, such aswhether a predetermined threshold amount of time has been exceeded(e.g., three months since an alert was first triggered), and/or howoften certain safety warnings (e.g., dynamic stability control warnings,anti-lock braking system warnings, etc.) are triggered.

As another example, driving behaviors identification unit 80 or anotherunit of data analysis unit 74 may determine a difference in time betweena maintenance service being performed on a vehicle (e.g., oil change,rotation and/or balancing of tires, belt checks, filter checks, etc.)and the suggested date for that service being performed (or a datecorresponding to a suggested mileage). The determination may be madeusing known, suggested maintenance dates and/or mileages, and data suchas an odometer reading (e.g., provided by on-board system 14 of FIG. 1 )and data indicative that a service was performed (e.g., from diagnosticdata 106 or third party data 114 of FIG. 2 , and/or from the driver oranother individual who uses a computing device to send a messageindicating that he or she performed the service, etc.), for example.

As yet another example, driving behaviors identification unit 80 oranother unit of data analysis unit 74 may determine a difference in timebetween (1) a recall notice being sent to the driver for a specificvehicle (e.g., via physical mail, via email, via SMS text message,and/or via a dedicated software application executing on a computingdevice of the driver) and (2) the driver or another individual takingthe vehicle in for servicing related to the recall notice. Thedetermination may be made using recall communication information, aswell as service data (e.g., date and type of a service that addressesthe recall), from third party data 114, for example.

Driver state information 158 may include driver attentiveness and/ordriver emotional state. For example, driving behaviors identificationunit 80 or another unit of data analysis unit 74 may determine howattentive a driver is (e.g., gaze direction, how often he or she checksinstruments and/or the rearview mirror, etc.) by using image recognitionand/or other image processing techniques to process driver image datafrom sensor data 104 of FIG. 2 . As another example, driving behaviorsidentification unit 80 or another unit of data analysis unit 74 maydetermine a driver’s emotional state and/or level of attentiveness(e.g., calm, angry, distracted, etc.) by using image recognition and/orother image processing techniques to process driver image data fromsensor data 104.

Other information 160 may include whether vehicle software (e.g.,software executed by on-board system 14 of FIG. 1 to control some or allof the operation of on-board system 14) is up-to-date, and/orlocation-based risk averseness (e.g., whether the driver tends to avoidareas with higher crime rates). For example, driving behaviorsidentification unit 80 or another unit of data analysis unit 74 maydetermine whether a driver has had his or her vehicle serviced toinstall a latest software version/update using software version datafrom diagnostic data 106 of FIG. 2 , and also using a known, currentsoftware version. As another example, driving behaviors identificationunit 80 or another unit of data analysis unit 74 may determine howoften, how long, and/or at what times of day a driver drives inrelatively high-crime areas using vehicle and/or mobile device GPS datafrom location data 110, and/or police blotter information from thirdparty data 114.

Some or all of the types of profile information discussed above, and/orother types of information, may be used (e.g., by profilegeneration/update unit 82 of FIG. 1 ) to populate and/or update one ormore profile fields for a particular driver. For example, profilegeneration/update unit 82 may use some types of profile informationwithin driving behavior information 152 and/or alert responsivenessinformation 156 as profile field values, and also calculate a“responsibility rating” based upon driving behavior information 152,feature usage information 154, alert responsiveness information 156,driver state information 158, and/or other information 160. Whencalculating a responsibility rating, various profile information typesand/or categories may be more heavily weighted than others. For example,compliance with speed limits may be weighted more heavily thanresponsiveness to malfunction/service indicators, and responsiveness tomalfunction/service indicators may be weighted more heavily thanweather-specific windshield wiper usage, etc. Generally, specific typesof profile information may be used to determine the responsibilityrating if it is known a priori (e.g., from past correlations with driveractions) or believed that those types of information are probative ofhow trustworthy or responsible the driver is.

The responsibility rating, and/or other fields of the driver profile,may also be affected by other types of profile information, includingtypes of information not shown in FIG. 2 . For example, theresponsibility rating may be determined using various types ofinformation shown in FIG. 3 , and also using information about thedriver and/or vehicle (e.g., data included in driver-provided data 112of FIG. 2 , such as age, gender, education level, profession, vehiclemodel, etc.). As just one more specific example, the responsibilityrating (or other information in a driver profile) may be based at leastin part upon a joint consideration of (1) a color of the vehicle, (2)times of day when the vehicle is driven, and (3) weather in which thevehicle is driven (e.g., in view of the assumption or known correlationthat vehicles of certain colors may be less visible at certain times ofday and/or in certain types of weather).

Iv. Exemplary Use Cases for Driver Profiles

Once a driver profile is determined (e.g., generated or updated usingsome or all of the profile information shown in FIG. 3 , and/or othertypes of information), one or more fields of the profile may be used inany of a number of different ways, depending upon the embodiment. Twouse cases, relating to the identification of suggested vehicles orvehicle components, have already been discussed above in connection withvehicle identification unit 84 and vehicle component identification unit86 of FIG. 1 .

In other embodiments, the driver profile may be used in connection withdriver education and/or licensing. For example, situation-specificdriving behaviors reflected in the profile (e.g., driving behavior inspecific types of weather and/or traffic) may be used by a governmententity for licensing or re-licensing of drivers. As another example,driver profiles may be used to rate how well or responsibly a drivinginstructor drives, and/or how well or responsibly his or her studentsdrive (with the latter ratings potentially also being used to rate theinstructor). In embodiments such as these, driver profile informationmay be transmitted to a remote computing system (e.g., third partyserver 18 of FIG. 1 ) for display to one or more individuals positionedto act upon the information (e.g., to approve the grant of a license, orprovide a performance review to an instructor, etc.).

In still other embodiments, driver profiles may be used to adjust costsfor usage-based insurance and/or other insurance premiums. For example,an underwriting department of an insurer may use driver profileinformation to gauge risk and set appropriate premiums. Alternatively,the costs of usage-based insurance may be automatically calculated by acomputing system (e.g., computer system 16 of FIG. 1 ) based upon thedriver profile information.

In still other embodiments, driver profiles may be used to influenceresale values of vehicles. In particular, driver profile informationindicative of how aggressively or conservatively the driver drove thevehicle may cause the value to go down or up, respectively. Inembodiments such as these, driver profile information may be transmittedto a remote computing system (e.g., third party server 18 of FIG. 1 , ora personal computing device of a potential buyer, etc.) for display toone or more individuals positioned to act upon the information (e.g.,set the vehicle resale price, or buy the vehicle).

In still other embodiments, driver profiles may be used by fleet ownersto provide rental vehicle discounts. For example, driver profileinformation may be transmitted to a remote computing system (e.g., thirdparty server 18 of FIG. 1 ) for display to one or more individualspositioned to act upon the information (e.g., an agent who can apply thediscount), or to cause the discount to be automatically applied to arental fee.

In still other embodiments, driver profiles may be used by car sharingservices to provide discounts. For example, driver profile informationmay be transmitted to a remote computing system (e.g., third partyserver 18 of FIG. 1 ) for display to one or more individuals positionedto act upon the information (e.g., an agent who can apply the discount),or to cause the discount to be automatically applied to a car share fee.

In still other embodiments, driver profiles may be used for otherpurposes, such as determining how a particular individual would likelycare for or maintain an autonomous vehicle, estimating how long vehiclecomponents (e.g., tires, brake pads, rotors, etc.) will last, and so on.

In some embodiments where driver profiles include responsibility ratings(as discussed above), such ratings may be used in a number of differentsituations where the driver’s trustworthiness is important. For example,the responsibility rating may be used by a credit rating entity to raiseor lower the driver’s credit score. In embodiments such as these, driverresponsibility ratings may be transmitted to a remote computing system(e.g., third party server 18 of FIG. 1 ) for display to one or moreindividuals positioned to act upon the information (e.g., authorize acredit score change), and/or for automated adjustment of the creditscore.

As another example, the responsibility rating may be submitted to anemployer in connection with a resume and/or application for a particularjob. A responsibility rating may be especially pertinent to jobs thatinvolve frequent driving, such as a driver for restaurant delivery, aride-sharing driver, etc. In embodiments such as these, a driverresponsibility rating may be transmitted to a remote computing system(e.g., third party server 18 of FIG. 1 ) for display to one or moreindividuals positioned to act upon the information (e.g., hire theindividual associated with the responsibility rating).

As yet another example, the responsibility rating may be used to enable“IOUs” with particular service providers (e.g., a taxi service,ride-sharing service, etc.). In embodiments such as these,responsibility ratings of driver profiles may be transmitted to a remotecomputing system (e.g., third party server 18 of FIG. 1 ), after whichthe computing system may indicate to one or more agents of the serviceprovider that an IOU may be accepted from the individual.

V. Exemplary Mapping of Driver Profile to Suggested Vehicles

FIG. 4 depicts an exemplary mapping 200 of a driver profile 202 tocriteria associated with particular types of vehicles. As used herein, avehicle “type” may correspond to a particular make, model, and/or year,for example. The mapping 200 may be used by vehicle identification unit84 of FIG. 1 to identify one or more vehicle types that are well-suitedto the driver for one or more reasons. For example, the mapping 200 maybe used to identify one or more vehicles that have characteristics thatmatch a driving style of an individual, and/or are less likely to haveproblems in view of the individual’s driving style.

Once a particular vehicle or vehicles has/have been identified, thevehicle(s) may be presented as a suggested vehicle for the individual(e.g., by computer system 16 of FIG. 1 causing a display of computersystem 16 to display the suggested vehicle(s), and/or transmitting dataindicative of the suggested vehicle(s) to another, remote computersystem for display, etc.). The suggestion(s) may be useful to thedriver, an auto dealer wishing to target its advertising, and/or an automanufacturer wishing to collect data for market research, for example.

In the mapping 200, information in the driver profile 202 is comparedagainst first criteria 204A associated with a first vehicle type (e.g.,a first make, model, and/or year of vehicle), and against secondcriteria 204B associated with a second vehicle type (e.g., a secondmake, model, and/or year of vehicle). While FIG. 4 only shows thecriteria of two types of vehicles, it is understood that driver profile202 may be compared against the criteria of additional different vehicletypes (e.g., 5, 10, 100, etc.). Further, in some embodiments, criteria204A and/or criteria 204B may include more, fewer, and/or differenttypes of criteria than are shown in FIG. 4 .

Driver profile 202 (e.g., a driver profile included in driver profiledatabase 76 of FIG. 1 ) may include driving behavior information 210,feature usage information 212, and alert responsiveness information 214,which may correspond to driving behavior information 152, feature usageinformation 154, and alert responsiveness information 156, respectively,of FIG. 3 . In the example mapping 200, the first criteria 204A and thesecond criteria 204B include the same general types of criteria: powercriteria 220A (or 220B), braking criteria 222A (or 222B), handlingcriteria 224A (or 224B), feature criteria 226A (or 226B), andruggedness/reliability criteria 228A (or 228B). In other embodiments,the first criteria 204A and second criteria 204B may have differentnumbers and/or types of criteria.

Power criteria 220A and/or 220B may include one or more criteriarelating to acceleration patterns, engine RPM patterns, and/or otherpatterns that may be indicative of how much a driver values or needs apowerful (e.g., high horsepower) vehicle. For example, power criteria220A and/or 220B may include a minimum frequency with which a vehicle isdriven with at least some threshold acceleration (as an absolute value,or as a percentage of a maximum possible acceleration for the vehiclebeing driven, etc.), and/or a requirement that engine RPMs fall (withsome threshold frequency) within certain ranges at different points intime when accelerating from a stop to a given speed.

As shown by arrows in FIG. 4 , driving behavior information 210 (e.g.,determined acceleration patterns, etc.) in driver profile 202 may beused to determine whether power criteria 220A and/or 220B are satisfied.If the first criteria 204A are associated with a sedan having afour-cylinder engine and the second criteria 204BV are associated with asedan having a six- or eight-cylinder engine, for example, drivingbehavior information 210 that is indicative of more aggressiveacceleration patterns might meet power criteria 220B but fail to meetpower criteria 220A.

Braking criteria 222A and/or 222B may include one or more criteriarelating to braking patterns, and/or other patterns that may beindicative of how important good (e.g., fast, reliable) braking abilityis to a driver. For example, braking criteria 222A and/or 222B mayinclude a set of minimum and/or maximum average tailgating distances,each corresponding to a different speed range, with the assumption beingthat a driver who follows other vehicles closely at higher speeds mayneed highly responsive and reliable braking ability. As shown by arrowsin FIG. 4 , driving behavior information 210 (e.g., average tailgatingdistances, braking patterns, etc.) in driver profile 202 may be used todetermine whether braking criteria 220A and/or 220B are satisfied.

Handling criteria 224A and/or 224B may include one or more criteriarelating to cornering patterns, and/or other patterns that may beindicative of how important good handing performance is to a driver. Forexample, handling criteria 224A and/or 224B may include minimum averagespeeds for different turn radii, and/or specifications of accelerationpatterns throughout turns having different radii, etc., with theassumption being that a driver who takes turns and/or curves in the roadaggressively may need or prefer a vehicle with good handlingperformance. As shown by arrows in FIG. 4 , driving behavior information210 (e.g., cornering patterns, possibly for specific types of roadsurface materials, etc.) in driver profile 202 may be used to determinewhether handling criteria 224A and/or 224B are satisfied.

Feature criteria 226A and/or 226B may include one or more criteriarelating to vehicle feature usage, and/or other patterns that may beindicative of how important various vehicle features are to a driver.For example, feature criteria 226A and/or 226B may include a minimumfrequency and/or length of use for cruise control usage, entertainmentsystem usage, automatic vehicle door opener usage, power seat controlusage, etc., with the assumption being that a driver who uses aparticular feature often and/or for long time periods may prefer avehicle with those features. As shown by arrows in FIG. 4 , featureusage information 212 in driver profile 202 may be used to determinewhether feature criteria 226A and/or 226B are satisfied.

Ruggedness/reliability criteria 228A and/or 228B may include one or morecriteria relating to how responsive a driver is to alerts/warnings,and/or other patterns that may be indicative of how well a drivermaintains a vehicle. For example, ruggedness/reliability criteria 228Aand/or 228B may include maximum time periods for responding to varioustypes of alerts (e.g., a check engine or low tire pressure alert, ifsuch alerts have occurred), with the assumption being that a driver whodoes not respond to certain types of alerts in a reasonable amount oftime may need or prefer a vehicle that is known to be more rugged orreliable (e.g., statistically requires less repair and/or maintenance).As shown by arrows in FIG. 4 , alert responsiveness information 214 indriver profile 202 may be used to determine whetherruggedness/reliability criteria 228A and/or 228B are satisfied.

In some embodiments, vehicle identification unit 84 of FIG. 1 maydetermine that driver profile 202 satisfies first criteria 204A (orsecond criteria 204B) if and only if driver profile 202 satisfies all ofthe individual types of criteria 220A through 228A (or 220B through228B). In other embodiments, other rules for satisfying first criteria204A and/or second criteria 204B are used. For example, vehicleidentification unit 84 may determine that driver profile 202 satisfiesfirst criteria 204A (or second criteria 204B) if and only if driverprofile 202 satisfies four of five of the individual types of criteria220A through 228A (or 220B through 228B). As another example, vehicleidentification unit 84 may assign a score based upon how well driverprofile 202 meets the individual types of criteria 220A through 228A (or220B through 228B), and determine whether the criteria 204A (or 204B)are satisfied based upon whether a total score (summing the individualscores) exceeds a predetermined threshold.

In some embodiments, only a fixed number of vehicle types (e.g., the Ntypes with the highest total score(s), or with the most matching typesof criteria, etc., where N is an integer greater than zero) can beidentified for a particular driver profile 202. In other embodiments, avariable number of vehicle types can be identified, so long as therespective criteria are satisfied. Once one or more vehicle types havebeen identified, vehicle identification unit 84 may cause the identifiedtype(s) to be displayed as vehicle suggestions, as discussed above inconnection with FIG. 1 .

VI. Exemplary Mapping of Driver Profile to Suggested Vehicle Components

FIG. 5 depicts an exemplary mapping 250 of a driver profile 252 tocriteria associated with particular types of vehicle components. As usedherein, a vehicle component “type” may correspond to a particular brandand/or part number of a particular component (e.g., brake pads, rotors,tires, etc.), for example. The mapping 250 may be used by vehiclecomponent identification unit 86 of FIG. 1 to identify one or morevehicle component types that are well-suited to the driver for one ormore reasons. For example, the mapping 250 may be used to identify oneor more vehicle components that have characteristics that match adriving style of an individual, and/or are less likely to have problemsin view of the individual’s driving style.

Once a particular vehicle component or components has/have beenidentified, the component(s) may be presented as a suggested componentfor the individual (e.g., by computer system 16 of FIG. 1 causing adisplay of computer system 16 to display the suggested component(s),and/or transmitting data indicative of the suggested component(s) toanother, remote computer system for display, etc.). The suggestion(s)may be useful to the driver, an auto parts dealer wishing to target itsadvertising, and/or an auto parts manufacturer wishing to collect datafor market research, for example.

In the mapping 250, information in the driver profile 252 is comparedagainst first criteria 254A associated with a first component type(e.g., a first brand or part number), and against second criteria 254Bassociated with a second component type (e.g., a second brand or partnumber). While FIG. 5 only shows the criteria of two types of vehiclecomponents, it is understood that driver profile 252 may be comparedagainst the criteria of additional component types (e.g., 5, 10, 20,etc.). Further, in some embodiments criteria 254A and/or criteria 254Bmay include more, fewer, and/or different types of criteria than areshown in FIG. 5 .

Driver profile 252 (e.g., a driver profile included in driver profiledatabase 76 of FIG. 1 ) may include driving behavior information 260 andalert responsiveness information 262, which may correspond to drivingbehavior information 152 and alert responsiveness information 156,respectively, of FIG. 3 . In the example mapping 250, the first criteria254A and the second criteria 254B include the same general types ofcriteria: performance criteria 270A (or 270B) and ruggedness/reliabilitycriteria 272A (or 272B). In other embodiments, the first criteria 254Aand second criteria 254B may have different numbers and/or types ofcriteria.

Performance criteria 270A and/or 270B may include one or more criteriarelating to acceleration patterns, braking patterns, cornering patterns,tailgating patterns, and/or other patterns that may be indicative of howmuch a driver is likely to need a particular level of performance orparticular performance characteristics. For example, performancecriteria 270A and/or 270B may include a minimum average tailgatingdistance at each of a number of different speeds, minimum average speedsfor different turn radii, and/or specifications of acceleration patternsthroughout turns having different radii, etc., with the assumption beingthat a driver who tends to follow other vehicles at a short distance mayneed higher-performance tires, brake pads and/or rotors, or that adriver who takes turns and/or curves in the road aggressively may needtires that grip the road better (e.g., tires with a particular treadand/or made of a particular material), etc. As shown by arrows in FIG. 5, driving behavior information 260 (e.g., determined accelerationpatterns, tailgating distances, etc.) in driver profile 252 may be usedto determine whether performance criteria 270A and/or 270B aresatisfied.

Ruggedness/reliability criteria 272A and/or 272B may include one or morecriteria relating to acceleration patterns, braking patterns, and/orcornering patterns (and/or other patterns that may be indicative of howmuch wear and tear a driver may cause to particular vehicle components),and/or may include one or more criteria relating to how responsive adriver is to alerts/warnings (and/or other patterns that may beindicative of how well a driver maintains a vehicle). For example,ruggedness/reliability criteria 272A and/or 272B may include a averagebraking distance to reach zero miles per hour for each of a number ofdifferent starting speeds, and/or average speed for each of a number ofdifferent turn radii, with the assumption being that a driver who brakesmore forcefully (and/or takes turns/corners more aggressively) may needor desire vehicle components (e.g., tires, brake pads, rotors, etc.)that do not wear or malfunction as easily. As another example,ruggedness/reliability criteria 272A and/or 272B may also (or instead)include maximum time periods for responding to various types of alerts(e.g., a check engine or low tire pressure alert, if such alerts haveoccurred), with the assumption being that a driver who does not respondto certain types of alerts in a reasonable amount of time may need orprefer a vehicle component that is known to be more rugged, reliable,and/or longer lasting. As shown by arrows in FIG. 5 , alertresponsiveness information 262 in driver profile 252 may be used todetermine whether ruggedness/reliability criteria 272A and/or 272B aresatisfied.

In some embodiments, vehicle identification unit 84 of FIG. 1 maydetermine that driver profile 252 satisfies first criteria 254A (orsecond criteria 504B) if and only if driver profile 252 satisfies bothof the individual types of criteria 270A and 272A (or 270B and 272B). Inother embodiments, other rules for satisfying first criteria 254A and/orsecond criteria 254B are used. For example, vehicle identification unit84 may assign a score based upon how well driver profile 252 meets theindividual types of criteria 270A and 272A (or 270B and 272B), anddetermine whether the criteria 254A (or 254B) are satisfied based uponwhether a total score (summing the individual scores) exceeds apredetermined threshold.

In some embodiments, only a fixed number of vehicle component types(e.g., the N types with the highest total score(s), or with the mostmatching types of criteria, etc., where N is an integer greater thanzero) may be identified for a particular driver profile 252. In otherembodiments, a variable number of vehicle component types may beidentified, so long as the respective criteria are satisfied. Once oneor more vehicle component types have been identified, vehicleidentification unit 84 may cause the identified component type(s) to bedisplayed as vehicle component suggestions, as discussed above inconnection with FIG. 1 .

VII. Exemplary Computer-Implemented Method for Detecting and Acting UponResponsiveness to Vehicle Alerts

FIG. 6 is a flow diagram of an exemplary computer-implemented method 300for detecting and acting upon driver responsiveness to vehicle alerts.The method 300 may be implemented by data analysis unit 74 or dataprocessing unit 54 of FIG. 1 , for example.

In the method 300, it may be determined that an on-board system of avehicle (e.g., on-board system 14 of vehicle 12 in FIG. 1 ) hasindicated, to a driver of the vehicle at a first time, that a subsystemof the vehicle requires repair, service, or maintenance (block 302). Forexample, it may be determined that the on-board system indicated a lowoil level, that a tire pressure was out of a recommended range, or thatthe engine should be checked. The time may be determined as a specifictime (e.g., corresponding to a time stamp), or a time range (e.g., on orbefore a particular date), for example.

In some embodiments and/or scenarios, block 302 may include receivingvehicle data that was generated by the on-board system of the vehicle(e.g., by diagnostic subsystem 46 of on-board system 14 in FIG. 1 ). Thevehicle data may include one or more diagnostic fault codes, and mayfurther include a plurality of time stamps associated with thediagnostic fault code(s). In one embodiment where the method 300 isimplemented by a server remote from the vehicle (e.g., a server ofcomputer system 16 of FIG. 1 ), the vehicle data may be received at theserver, from the on-board system, via a wireless link (e.g., via network20 of FIG. 1 ).

An amount of time that has elapsed since the first time without thesubsystem being repaired, serviced, or maintained may be detected (block304). If time stamps were received with vehicle data at block 302, block304 may include calculating a time difference between two of the timestamps (e.g., an earliest time stamp associated with a diagnostic codeindicating the presence of a check engine or other alert, and anearliest time stamp associated with a diagnostic code indicating theabsence of that same alert). In a scenario where the subsystem was notserviced prior to some predetermined threshold length of time (e.g., onemonth, three months, etc.), the detected amount of time may be thethreshold length of time.

Based upon the determination at block 304, a driver profile associatedwith the driver (e.g., in driver profiles database 76 of FIG. 1 ) may beadjusted to reflect that a sufficiently small amount of time has elapsed(block 306). Block 306 may correspond to the generation of a new driverprofile and/or new driver profile fields, or to the update of anexisting driver profile.

Transmission, to a particular entity, of at least the portion of thedriver profile that was set at block 306 may be caused to occur (block308), e.g., by generating an instruction to transmit the profile or aprofile portion. The entity may be an entity (e.g., financialinstitution) that improves a credit rating associated with the driverbased upon the profile or profile portion, an entity (e.g., an insurer)that improves an insurance rating associated with the driver based uponthe profile or profile portion, an entity (e.g., an employer) thatreviews the profile or profile portion in connection with a job soughtby the driver, or an entity (e.g., a rental vehicle company, taxiservice, etc.) that offers a permanent or temporary credit (e.g., adiscount or IOU), in connection with a good or service offered by theentity based upon the profile or profile portion, for example.

In some embodiments, the method 300 may include one or more blocks notshown in FIG. 6 . For example, the method 300 may include an additionalblock, between blocks 304 and 306, at which it is determined that theamount of time elapsed since the time of an earliest time stampassociated with a diagnostic code indicating the presence of a checkengine or other alert is greater than a predetermined threshold amountof time (as discussed above). In such an embodiment, block 306 mayinclude lowering a rating (e.g., responsibility rating) of the driverprofile in response to determining that the amount of time elapsed isgreater than the pre-determined threshold amount of time.

As another example, the method 300 may include a first additional blockat which telematics data (e.g., operational data indicative of how thedriver operates the vehicle) collected by one or more electronicsubsystems located on or in the vehicle, and/or collected by a mobileelectronic device of the driver or a passenger, is received, and asecond additional block at which the received telematics data isanalyzed to identify driving behaviors of the driver. In such anembodiment, block 306 may include setting the profile or profile portionbased upon the detected amount of time elapsed, and further based uponthe identified driving behaviors. The method may include additional,less, or alternate actions, including those discussed elsewhere herein.

VIII. Exemplary Computer-Implemented Method for Detecting and ActingUpon Driver Compliance with Driver-Specific Limitations

FIG. 7 is a flow diagram of an exemplary computer-implemented method 320for detecting and acting upon driver compliance with driver-specificlimitations. The method 320 may be implemented by data analysis unit 74or data processing unit 54 of FIG. 1 , for example.

In the method 320, it may be determined that a driver of a vehicle hasone or more limitations specific to a medical condition, and/or physicalcharacteristic, of the driver (block 322). For example, it may bedetermined that the driver has impaired vision (e.g., shortsightednessor poor night vision), that the driver has impaired motor skills (e.g.,causing slow reaction times), and so on. Block 322 may includerequesting one or more records from a remote server via a network (e.g.,from third party server 18 of FIG. 1 via network 20), for example.

Telematics data, collected during one or more time periods by one ormore subsystems located on or in the vehicle, or a by mobile electronicdevice running a telematics data gathering or generating application,may be received (block 324). The telematics data may include sensor data(e.g., data from external sensor 30 and/or external sensor 32 of FIG. 1, and/or from a sensor of a mobile electronic device, etc.), and may beindicative of an environment external to the vehicle during the timeperiod(s) in which the telematics data was collected by the vehiclesubsystem(s). As another example, the telematics data may includeoperational data indicative of speeds of the vehicle during the timeperiod(s).

The telematics data received at block 324 may be analyzed to identify aplurality of driving behaviors that the driver exhibited during the timeperiod(s) in which the telematics data was collected (block 326). If thetelematics data includes sensor data indicative of the externalenvironment of the vehicle, for example, the sensor data may be analyzedto determine distances, during the time period(s), between the vehicleand other vehicles (e.g., other vehicles in front of the vehicle atvarious times).

Based at least upon the driving behaviors identified at block 326, alevel of compliance with the limitation(s), during the time period(s) inwhich the telematics data was collected, may be determined (block 328).If distances to other vehicles were determined at block 326, forexample, block 328 may include calculating one or more metrics based atleast upon those distances, and determining the level of compliance atleast in part based upon the calculated metric(s) and known correlationsbetween “safe” distances and limitations of the sort exhibited by thedriver.

Based upon the determination at block 328, a driver profile associatedwith the driver may be adjusted to reflect a satisfactory level ofcompliance (block 330). Block 330 may correspond to the generation of anew driver profile and/or new driver profile fields, or to the update ofan existing driver profile.

Transmission, to a particular entity, of at least the portion of thedriver profile may be caused to occur (block 332), e.g., by generatingan instruction to transmit the profile or profile portion. The entitymay be an entity (e.g., financial institution) that improves a creditrating associated with the driver based upon the profile or profileportion, an entity (e.g., an insurer) that improves an insurance ratingassociated with the driver based upon the profile or profile portion, anentity (e.g., an employer) that reviews the profile or profile portionin connection with a job sought by the driver, or an entity (e.g., arental vehicle company, taxi service, etc.) that offers a permanent ortemporary credit (e.g., a discount or IOU), in connection with a good orservice offered by the entity based upon the profile or profile portion,for example. The method may include additional, less, or alternateactions, including those discussed elsewhere herein.

IX. Exemplary Computer-Implemented Method for Detecting and Acting UponDriver Behavior While Driving with Passengers

FIG. 8 is a flow diagram of an exemplary computer-implemented method 340for detecting and acting upon driver behavior while driving withpassengers. The method 340 may be implemented by data analysis unit 74or data processing unit 54 of FIG. 1 , for example.

In the method 340, telematics data, collected by one or more electronicsubsystems located on or in a vehicle, and/or by a mobile electronicdevice of a driver or passenger in the vehicle, may be received (block344). The telematics data may include image data that was collected by acamera mounted in the vehicle (e.g., a camera of internal sensor(s) 38of FIG. 1 ), weight sensor data that was collected by one or more weightsensors installed within one or more seats of the vehicle (e.g., one ormore weight sensors of internal sensor(s) 38), seat belt data that wasgenerated by an on-board system of the vehicle (e.g., on-board system14), operational data of the vehicle, sensor data indicative of anenvironment external to the vehicle, and/or other data.

The telematics data received at block 344 may be analyzed to identifyone or more time periods during which a driver of the vehicle drove withone or more passengers, and to identify one or more driving behaviors ofthe driver during the identified time period(s) (block 346). As oneexample, in some embodiments where the telematics data includes imagedata collected by a camera mounted within the vehicle, block 346 mayinclude applying an image recognition algorithm to the image data todetermine when passengers were within the vehicle. As another example,in some embodiments where the telematics data includes weight sensordata collected by one or more weight sensors installed in seats, block346 includes analyzing the weight sensor data to determine whenpassengers were within the vehicle. As yet another example, in someembodiments where the telematics data includes seat belt data generatedby an on-board system of the vehicle, block 346 includes analyzing theseat belt data to determine when passengers were within the vehicle.

In some embodiments where the telematics data includes sensor dataindicative of an environment external to the vehicle (i.e., theenvironment during the time periods in which one or more passengers werepresent), block 346 includes analyzing the sensor data to identify atleast one of the one or more driving behaviors. Additionally oralternatively, in some embodiments where the telematics data includesoperational data indicative of how the driver operated the vehicle,block 346 includes analyzing the operational data to identify at leastone of the driving behaviors.

Generally, the driving behaviors may be indicative of how much care wastaken by the driver while carrying one or more passengers. For example,the driving behaviors may include average distances between the vehicleand other vehicles during the identified period(s), lane usage of thevehicle during the identified time period(s), and/or any other suitabledriving behaviors, including any of those discussed in connection withFIG. 1 or FIG. 3 . In some embodiments, like driving behaviors are alsoidentified for times when no passengers are carried, e.g., to allow adetermination of how the driver modifies his or her driving whenentrusted with passengers.

Based upon the time period(s) and driving behavior(s) identified atblock 346, a driver profile associated with the driver may be adjustedto reflect risk-averseness of the driving behavior(s) during the timeperiod(s) (block 348). Block 348 may correspond to the generation of anew driver profile and/or new driver profile fields, or to the update ofan existing driver profile. In some embodiments, block 346 includesdetermining a specific number of passengers during each of theidentified time periods, and block 348 includes adjusting the profilebased not only upon the driving behavior(s) during the identified timeperiod(s), but also based upon on the specific number of passengersduring each of those time periods. As indicated above, the profile orprofile portion may also, or instead, be adjusted based upon how thedriver modifies his or her driving compared to when he or she drivesalone.

Transmission, to a particular entity, of at least the portion of thedriver profile may be caused to occur (block 350), e.g., by generatingan instruction to transmit the profile or profile portion. The entitymay be an entity (e.g., financial institution) that improves a creditrating associated with the driver based upon the profile or profileportion, an entity (e.g., an insurer) that improves an insurance ratingassociated with the driver based upon the profile or profile portion, anentity (e.g., an employer) that reviews the profile or profile portionin connection with a job sought by the driver, or an entity (e.g., arental vehicle company, taxi service, etc.) that offers a permanent ortemporary credit (e.g., a discount or IOU), in connection with a good orservice offered by the entity, based upon the profile or profileportion, for example. As a result, risk-averse drivers may be offeredbenefits or cost savings. The method may include additional, less, oralternate actions, including those discussed elsewhere herein.

X. Exemplary Computer-Implemented Method for Identifying a SuggestedVehicle For a Driver

FIG. 9 is a flow diagram of an exemplary computer-implemented method 400for identifying a suggested vehicle for a driver. The method 400 may beimplemented by data analysis unit 74 or data processing unit 54 of FIG.1 , for example.

In the method 400, telematics data, collected during one or more timeperiods by one or more electronic subsystems located on or in a vehicle,and/or by a mobile electronic device (such as a mobile device running atelematics data gathering application), may be received (block 402). Thetelematics data may include operational data indicative of how a driveroperated the vehicle during the time period(s). The telematics data mayalso include data indicative of how and/or how often the driver used oneor more features of the vehicle during the time period(s), sensor dataindicative of an environment external to the vehicle during the timeperiod(s), and/or other data, for example.

The telematics data received at block 402 may be analyzed to identifyone or more driving behaviors of the driver during the one or more timeperiods (block 404). The driving behavior(s) may include accelerationpatterns, braking patterns, and/or cornering patterns of the driver, forexample. As another example, the driving behavior(s) may includedistances between the vehicle and other vehicles (e.g., tailgatingdistance) during the time period(s). As yet another example, the drivingbehavior(s) may include driving behaviors, during the time period(s),that took place in specific weather conditions (e.g., weather conditionsas identified based upon sensor data included in the telematics data).

Based at least upon the driving behavior(s) identified at block 404, adriver profile associated with the driver may be generated or modified(block 406). The profile may be caused to indicate an accelerationpreference, braking preference, and/or cornering preference of thedriver (e.g., by way of indicating the frequent occurrence of certainacceleration, braking, and/or cornering patterns for the driver), forexample. As another example, the profile may be caused to indicate oneor more preferred features (e.g., by way of indicating frequent driverusage of those features), and/or a preferred level of reliability orruggedness (e.g., by way of indicating the driver’s tendencies toaddress repair, service, and/or maintenance issues in a timely oruntimely manner).

Based at least upon the driver profile that was generated or modified atblock 406, a suggested vehicle type (e.g., make, model, and/or year) maybe identified (block 408). The identification at block 408 may be madeat least in part by determining that the driver profile meets a set ofone or more matching criteria associated with the suggested vehicletype. For example, block 408 may include determining that a certainmatching score is achieved. As another example, block 408 may includedetermining that an acceleration preference of the driver meets a firstcriterion of the set of matching criteria, that a braking preference ofthe driver meets a second criterion of the set of matching criteria,and/or that a cornering preference of the driver meets a third criterionof the set of matching criteria.

As yet another example, block 408 may include determining that thesuggested vehicle type provides one or more preferred features asindicated in the driver profile, and/or that the suggested vehicle typehas a level of reliability that satisfies a preferred level ofreliability of the driver as indicated in the driver profile, etc. Insome embodiments, the suggested vehicle type may be identified bycausing the generated or modified driver profile to be transmitted to athird party (e.g., third party server 18 of FIG. 1 , via network 20),and receiving in response from the third party the indication of thesuggested vehicle type.

An indication of the suggested vehicle type may be caused to bedisplayed to a user (block 410), e.g., by generating an instruction todisplay the suggested vehicle type or an instruction to transmit amessage indicating the suggested vehicle type. The display may bepresented via a web browser application or dedicated applicationexecuted by a computing device of the user (e.g., the driver, by way oftransmitting, via a computer network, the indication of the suggestedvehicle type to a computing device of the driver), or may be presentedto an agent of a computing system implementing the method 400, forexample. The method may include additional, less, or alternate actions,including those discussed elsewhere herein.

Xi. Exemplary Computer-Implemented Method for Identifying A SuggestedVehicle Component For a Driver

FIG. 10 is a flow diagram of an exemplary computer-implemented method420 for identifying a suggested vehicle component for a driver. Themethod 420 may be implemented by data analysis unit 74 or dataprocessing unit 54 of FIG. 1 , for example.

In the method 420, telematics data, collected during one or more timeperiods by one or more electronic subsystems located on or in a vehicle,and/or by a mobile electronic device (e.g., by one or more sensors of amobile electronic device running a telematics application), may bereceived (block 422). The telematics data may include operational dataindicative of how a driver operated the vehicle during the timeperiod(s). The telematics data may also include sensor data indicativeof an environment external to the vehicle during the time period(s)and/or other data, for example.

The telematics data received at block 422 may be analyzed to identifyone or more driving behaviors of the driver during the one or more timeperiods (block 424). The driving behavior(s) may include accelerationpatterns, braking patterns, and/or cornering patterns of the driver, forexample. As another example, the driving behavior(s) may includedistances between the vehicle and other vehicles (e.g., tailgatingdistance) during the time period(s). As yet another example, the drivingbehavior(s) may include driving behaviors, during the time period(s),that took place in specific weather conditions (e.g., weather conditionsidentified based upon sensor data included in the telematics data).

Based at least upon the driving behavior(s) identified at block 424, adriver profile associated with the driver may be generated or modified(block 426). The profile may be caused to indicate an accelerationpreference, braking preference, and/or cornering preference of thedriver (e.g., by way of indicating the frequent occurrence of certainacceleration, braking, and/or cornering patterns for the driver), forexample. As another example, the profile may be caused to indicate apreferred level of reliability or ruggedness (e.g., by way of indicatingthe driver’s tendencies to address repair, service, and/or maintenanceissues in a timely or untimely manner).

Based at least upon the driver profile that was generated or modified atblock 426, a suggested vehicle component type (e.g., a specific partnumber, brand, etc., for tires, brake pads, rotors, or another vehiclecomponent) may be identified (block 428). The identification at block428 may be made at least in part by determining that the driver profilemeets a set of one or more matching criteria associated with thesuggested vehicle component type. For example, block 428 may includedetermining that a certain matching score is achieved. As anotherexample, block 428 may include determining that an accelerationpreference of the driver meets a first criterion of the set of matchingcriteria, that a braking preference of the driver meets a secondcriterion of the set of matching criteria, and/or that a corneringpreference of the driver meets a third criterion of the set of matchingcriteria. In some embodiments, the suggested vehicle component type maybe identified by causing the generated or modified driver profile to betransmitted to a third party (e.g., third party server 18 of FIG. 1 ,via network 20), and receiving in response from the third party theindication of the suggested vehicle component type.

An indication of the suggested vehicle component type may be caused tobe displayed to a user (block 430), e.g., by generating an instructionto display the suggested vehicle type or an instruction to transmit amessage indicating the suggested vehicle type. The display may bepresented via a web browser application or dedicated applicationexecuted by a computing device of the user (e.g., the driver, by way oftransmitting, via a computer network, the indication of the suggestedvehicle component type to a computing device of the driver), or may bepresented to an agent of a computing system implementing the method 420,for example. The method may include additional, less, or alternateactions, including those discussed elsewhere herein.

XII. Exemplary Computer System for Generating and/or Using DriverProfiles

FIG. 11 is a block diagram of an exemplary computer system 500 on whicha method may operate in accordance with any of the embodiments describedabove. The computer system 500 of FIG. 11 includes a computing device inthe form of a computer 510. Components of the computer 510 may include,but are not limited to, a processing unit 520, a system memory 530, anda system bus 521 that couples various system components including thesystem memory to the processing unit 520. The system bus 521 may be anyof several types of bus structures including a memory bus or memorycontroller, a peripheral bus, and a local bus using any of a variety ofbus architectures. By way of example, and not limitation, sucharchitectures include the Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnect (PCI) bus (also known as Mezzanine bus).

Computer 510 typically includes a variety of computer-readable media.Computer-readable media can be any available media that can be accessedby computer 510 and includes both volatile and nonvolatile media, andboth removable and non-removable media. By way of example, and notlimitation, computer-readable media may comprise computer storage mediaand communication media. Computer storage media includes volatile andnonvolatile, removable and non-removable media implemented in any methodor technology for storage of information such as computer readableinstructions, data structures, program modules or other data. Computerstorage media includes, but is not limited to, RAM, read only memory(ROM), EEPROM, FLASH memory or other memory technology, CD-ROM, digitalversatile disks (DVD) or other optical disk storage, magnetic cassettes,magnetic tape, magnetic disk storage or other magnetic storage devices,or any other medium which can be used to store the desired informationand which can accessed by computer 510. Communication media typicallyembodies computer-readable instructions, data structures, programmodules or other data in a modulated data signal such as a carrier waveor other transport mechanism and includes any information deliverymedia. The term “modulated data signal” means a signal that has one ormore of its characteristics set or changed in such a manner as to encodeinformation in the signal. By way of example, and not limitation,communication media includes wired media such as a wired network ordirect-wired connection, and wireless media such as acoustic, radiofrequency (RF), infrared and other wireless media. Combinations of anyof the above are also included within the scope of computer-readablemedia.

The system memory 530 includes computer storage media in the form ofvolatile and/or nonvolatile memory such as ROM 531 and RAM 532. A basicinput/output system (BIOS) 533, containing the basic routines that helpto transfer information between elements within computer 510, such asduring start-up, is typically stored in ROM 531. RAM 532 typicallycontains data and/or program modules that are immediately accessible to,and/or presently being operated on by, processing unit 520. By way ofexample, and not limitation, FIG. 11 illustrates operating system 534,application programs 535, other program modules 536, and program data537.

The computer 510 may also include other removable/non-removable,volatile/nonvolatile computer storage media. By way of example only,FIG. 11 illustrates a hard disk drive 541 that reads from or writes tonon-removable, nonvolatile magnetic media, a magnetic disk drive 551that reads from or writes to a removable, nonvolatile magnetic disk 552,and an optical disk drive 555 that reads from or writes to a removable,nonvolatile optical disk 556 such as a CD ROM or other optical media.Other removable/non-removable, volatile/nonvolatile computer storagemedia that can be used in the exemplary operating environment include,but are not limited to, magnetic tape cassettes, flash memory cards,digital versatile disks, digital video tape, solid state RAM, solidstate ROM, and the like. The hard disk drive 541 is typically connectedto the system bus 521 through a non-removable memory interface such asinterface 540, and magnetic disk drive 551 and optical disk drive 555are typically connected to the system bus 521 by a removable memoryinterface, such as interface 550.

The drives and their associated computer storage media discussed aboveand illustrated in FIG. 11 provide storage of computer-readableinstructions, data structures, program modules and other data for thecomputer 510. In FIG. 11 , for example, hard disk drive 541 isillustrated as storing operating system 544, application programs 545,other program modules 546, and program data 547. Note that thesecomponents can either be the same as or different from operating system534, application programs 535, other program modules 536, and programdata 537. Operating system 544, application programs 545, other programmodules 546, and program data 547 are given different reference numbersin FIG. 11 to illustrate that, at a minimum, they are different copies.A user may enter commands and information into the computer 510 throughinput devices such as a keyboard 562 and cursor control device 561,commonly referred to as a mouse, trackball or touch pad. A monitor 591or other type of display device is also connected to the system bus 521via an interface, such as a graphics controller 590. In addition to themonitor 591, computers may also include other peripheral output devicessuch as printer 596, which may be connected through an output peripheralinterface 595.

The computer 510 may operate in a networked environment using logicalconnections to one or more remote computers, such as a remote computer580. The remote computer 580 may be a personal computer, a server, arouter, a network PC, a peer device or other common network node, andtypically includes many or all of the elements described above relativeto the computer 510, although only a memory storage device 581 has beenillustrated in FIG. 11 . The logical connections depicted in FIG. 11include a local area network (LAN) 571 and a wide area network (WAN)573, but may also include other networks. Such networking environmentsare commonplace in hospitals, offices, enterprise-wide computernetworks, intranets and the Internet.

When used in a LAN networking environment, the computer 510 is connectedto the LAN 571 through a network interface or adapter 570. When used ina WAN networking environment, the computer 510 typically includes amodem 572 or other means for establishing communications over the WAN573, such as the Internet. The modem 572, which may be internal orexternal, may be connected to the system bus 521 via the input interface560, or via another appropriate mechanism. In a networked environment,program modules depicted relative to the computer 510, or portionsthereof, may be stored in the remote memory storage device 581. By wayof example, and not limitation, FIG. 11 illustrates remote applicationprograms 585 as residing on memory device 581.

The communications connections 570, 572 allow the device to communicatewith other devices. The communications connections 570, 572 are anexample of communication media, as discussed above.

The methods of any of the embodiments described above (e.g., methods300, 320, 340, 400, and/or 420) may be implemented wholly or in partusing one or more computer systems such as the computer system 500illustrated in FIG. 11 . Referring generally to the embodiments of FIG.1 , for example, the computer 510 may be used as some or all of computersystem 16, with the various units 80, 82, 84, and 86 being instructionsthat are a part of application programs 535 stored in RAM 532 and/orapplication programs 545 stored in hard disk drive 541. As anotherexample, data from on-board system 14 may be received via a modemsimilar to the modem 572, which may in turn be coupled to a networksimilar to network 20 of FIG. 1 . As another example, indications ofsuggested vehicle types and/or vehicle component types generated byvehicle identification unit 84 and/or vehicle component identificationunit 86 of FIG. 1 may be sent to a remote computing device (e.g., remotecomputer 580) for display to a user.

Xiii. Technical Advantages

The aspects described herein may be implemented as part of one or morecomputer components, such a server device, for example. Furthermore, theaspects described herein may be implemented within a computer networkarchitecture implementing vehicle telematics technology, and mayleverage that architecture and technology to obtain new and beneficialresults not previously achieved. Thus, the aspects described hereinaddress and solve issues of a technical nature that are necessarilyrooted in computer technology.

For instance, aspects described herein may include analyzing varioussources of vehicle data to identify certain driving behaviors that arenot captured or recognized by conventional systems, such as drivercompliance with driver-specific limitations (e.g., handicaps), drivingperformance in the presence of passengers, and driver responsiveness towarnings/alerts. Without the improvements provided by capturing suchdriving behaviors, the accurate assessment of risk, trustworthiness,etc. (as the case may be, depending upon the particular embodiment) mayrequire much larger samples of telematics data to be collected andprocessed. Naturally, this would result in additional memory usage,processing resources, and/or time. Thus, aspects described hereinaddress computer-related issues that are related to efficiency,processing, and storage metrics, such as consuming less power and/ormemory, for example.

Xiv. Exemplary Computer-Implemented Method Embodiments

In one aspect, a computer-implemented method for detecting and actingupon driver responsiveness to vehicle alerts may include: (1)determining, by one or more processors, that an on-board system of avehicle indicated, to a driver of the vehicle and at a first time, thata subsystem of the vehicle requires repair, service or maintenance; (2)detecting, by the one or more processors, an amount of time elapsedsince the first time without the subsystem being repaired, serviced ormaintained; (3) setting, by the one or more processors and based atleast upon the detected amount of time elapsed since the first time, atleast a portion of a driver profile associated with the driver; and/or(4) causing, by the one or more processors, transmission of at least theportion of the driver profile to an entity that (i) adjusts a creditrating associated with the driver based upon at least the portion of thedriver profile, (ii) adjusts an insurance rating associated with thedriver based upon at least the portion of the driver profile, (iii)reviews at least the portion of the driver profile in connection with ajob sought by the driver, and/or (iv) offers a permanent or temporarycredit, in connection with a good or service offered by the entity,based upon at least the portion of the driver profile. The method mayinclude additional, fewer, and/or alternate actions, including thosediscussed elsewhere herein.

For instance, in various aspects, determining that the on-board systemof the vehicle indicated that the subsystem of the vehicle requiresrepair, service or maintenance may include receiving vehicle datagenerated by the on-board system of the vehicle, the vehicle dataincluding one or more diagnostic fault codes.

Additionally or alternatively, the vehicle data may further include aplurality of time stamps associated with the one or more diagnosticfault codes, and detecting the amount of time elapsed since the firsttime may include calculating a time difference between two time stampsof the plurality of time stamps.

Additionally or alternatively, receiving the vehicle data may includereceiving the vehicle data from the on-board system of the vehicle, at aserver remote from the vehicle, via a wireless link.

Additionally or alternatively, determining that the on-board system ofthe vehicle indicated that the subsystem of the vehicle requires repair,service or maintenance may include determining that the on-board systemof the vehicle indicated to the driver that an oil level of the vehiclewas low.

Additionally or alternatively, determining that the on-board system ofthe vehicle indicated that the subsystem of the vehicle requires repair,service or maintenance may include determining that the on-board systemof the vehicle indicated to the driver that a tire pressure of thevehicle was out of a recommended range.

Additionally or alternatively, determining that the on-board system ofthe vehicle indicated that the subsystem of the vehicle requires repair,service or maintenance may include determining that the on-board systemof the vehicle provided a check engine indicator to the driver.

Additionally or alternatively, the method may include: determining, bythe one or more processors, that the amount of time elapsed since thefirst time is greater than a predetermined threshold amount of time,wherein setting at least the portion of the driver profile may includelowering a rating of the driver profile in response to determining thatthe amount of time elapsed since the first time is greater than thepre-determined threshold amount of time.

Additionally or alternatively, causing transmission of at least theportion of the driver profile to an entity may include causingtransmission of at least the portion of the driver profile to afinancial institution that adjusts the credit rating associated with thedriver based upon at least the portion of the driver profile.

Additionally or alternatively, causing transmission of at least theportion of the driver profile to an entity may include causingtransmission of at least the portion of the driver profile to anemployer that reviews at least the portion of the driver profile inconnection with the job sought by the driver.

Additionally or alternatively, causing transmission of at least theportion of the driver profile to an entity may include causingtransmission of at least the portion of the driver profile to an insurerthat adjusts the insurance rating of the driver based upon at least theportion of the driver profile.

Additionally or alternatively, causing transmission of at least theportion of the driver profile to an entity may include causingtransmission of at least the portion of the driver profile to a rentalvehicle company that discounts a car rental offered to the driver basedat least upon at least the portion of the driver profile.

Additionally or alternatively, the method may include: receivingtelematics data that was collected by one or both of (i) one or moreelectronic subsystems located on or in the vehicle and (ii) a mobileelectronic device of the driver or a passenger, wherein receiving thetelematics data includes receiving operational data indicative of howthe driver operated the vehicle; and analyzing, by the one or moreprocessors, the received telematics data to identify a plurality ofdriving behaviors of the driver, wherein setting at least the portion ofthe driver profile may include setting at least the portion of thedriver profile based at least upon (i) the detected amount of timeelapsed since the first time and (ii) the plurality of drivingbehaviors.

In another aspect, a computer-implemented method for detecting andacting upon driver compliance with driver-specific limitations mayinclude: (1) determining, by one or more processors, that a driver of avehicle has one or more limitations specific to one or both of (i) amedical condition of the driver, and (ii) a physical characteristic ofthe driver; (2) receiving telematics data that was collected during oneor more time periods by one or both of (i) one or more electronicsubsystems located on or in the vehicle and (ii) a mobile electronicdevice of the driver or a passenger; (3) analyzing, by the one or moreprocessors, the received telematics data to identify a plurality ofdriving behaviors of the driver during the one or more time periods; (4)determining, by the one or more processors and based at least upon theplurality of driving behaviors, a level of compliance with the one ormore limitations during the one or more time periods; (5) based at leastupon the determined level of compliance, setting, by the one or moreprocessors, at least a portion of a driver profile associated with thedriver; and/or (6) causing, by the one or more processors, transmissionof at least the portion of the driver profile to an entity that (i)adjusts a credit rating associated with the driver based upon at leastthe portion of the driver profile, (ii) adjusts an insurance ratingassociated with the driver based upon at least the portion of the driverprofile, (iii) reviews at least the portion of the driver profile inconnection with a job sought by the driver, and/or (iv) offers apermanent or temporary credit, in connection with a good or serviceoffered by the entity, based at least upon at least the portion of thedriver profile. The method may include additional, fewer, and/oralternate actions, including those discussed elsewhere herein.

For instance, in various aspects, determining that the driver has one ormore limitations includes determining that the driver has impairedvision. Additionally or alternatively, determining that the driver hasone or more limitations includes determining that the driver hasimpaired motor skills. Additionally or alternatively, determining thatthe driver has one or more limitations may include requesting one ormore records from a remote server via a network. Additionally oralternatively, receiving telematics data may include receiving sensordata indicative of an environment external to the vehicle during the oneor more time periods.

Additionally or alternatively, analyzing the received telematics data toidentify a plurality of driving behaviors of the driver may includeanalyzing the sensor data to determine a plurality of distances, duringthe one or more time periods, between the vehicle and other vehicles.Additionally or alternatively, determining the level of compliance withthe one or more limitations may include: calculating one or more metricsbased at least upon the plurality of distances; and determining thelevel of compliance based at least upon the one or more metrics. A highlevel of compliance may, in turn, entitle the driver or vehicle owner toan insurance discount or other insurance cost-savings.

Additionally or alternatively, receiving telematics data may includereceiving operational data indicative of a plurality of speeds of thevehicle during the one or more time periods. Additionally oralternatively, setting at least the portion of the driver profile mayinclude lowering a compliance rating of the driver profile in responseto determining that the level of compliance is below a pre-determinedthreshold level. As a result, risk averse drivers may receive insurancediscounts or insurance cost-savings.

Additionally or alternatively, causing transmission of at least theportion of the driver profile to an entity may include causingtransmission of at least the portion of the driver profile to afinancial institution that adjusts the credit rating associated with thedriver based upon at least the portion of the driver profile.

Additionally or alternatively, causing transmission of at least theportion of the driver profile to an entity may include causingtransmission of at least the portion of the driver profile to anemployer that reviews at least the portion of the driver profile inconnection with the job sought by the driver.

Additionally or alternatively, causing transmission of at least theportion of the driver profile to an entity may include causingtransmission of at least the portion of the driver profile to an insurerthat adjusts the insurance rating of the driver based upon at least theportion of the driver profile.

Additionally or alternatively, causing transmission of at least theportion of the driver profile to an entity may include causingtransmission of at least the portion of the driver profile to a rentalvehicle company that discounts a car rental offered to the driver basedupon at least the portion of the driver profile.

In another aspect, a computer-implemented method for detecting andacting upon driver behavior while driving with passengers may include:(1) receiving telematics data that was collected by one or both of (i)one or more electronic subsystems located on or in a vehicle and (ii) amobile electronic device of a driver or a passenger in the vehicle,, orcollected/generated by one or more mobile device sensors; (2) analyzing,by one or more processors, the received telematics data to (i) identifyone or more time periods during which the driver of the vehicle drovewith one or more passengers, and (ii) identify one or more drivingbehaviors of the driver during the one or more time periods; (3) basedat least upon the determined one or more driving behaviors of the driverduring the one or more time periods, setting, by the one or moreprocessors, at least a portion of a driver profile associated with thedriver; and/or (4) causing, by the one or more processors, transmissionof at least the portion of the driver profile to an entity that (i)adjusts a credit rating associated with the driver based upon at leastthe portion of the driver profile, (ii) adjusts an insurance ratingassociated with the driver based upon at least the portion of the driverprofile, (iii) reviews at least the portion of the driver profile inconnection with a job sought by the driver, and/or (iv) offers apermanent or temporary credit, in connection with a good or serviceoffered by the entity, based upon at least the portion of the driverprofile. The method may include additional, fewer, and/or alternateactions, including those discussed elsewhere herein.

For instance, in various aspects, receiving telematics data may includereceiving image data that was collected by a camera mounted within thevehicle, and analyzing the received telematics data to identify the oneor more time periods during which the driver drove with one or morepassengers may include applying an image recognition algorithm to theimage data to determine when passengers were within the vehicle.

Additionally or alternatively, receiving telematics data may includereceiving weight sensor data that was collected by one or more weightsensors installed within one or more seats of the vehicle, and analyzingthe received telematics data to identify the one or more time periodsduring which the driver drove with one or more passengers may includeanalyzing the weight sensor data to determine when passengers werewithin the vehicle.

Additionally or alternatively, receiving telematics data may includereceiving seat belt data that was collected by one or more sensorsinstalled within the vehicle, and analyzing the received telematics datato identify the one or more time periods during which the driver drovewith one or more passengers may include analyzing the seat belt data todetermine when passengers were within the vehicle.

Additionally or alternatively, receiving telematics data may includereceiving sensor data indicative of an environment external to thevehicle during the one or more time periods, and analyzing the receivedtelematics data to identify one or more driving behaviors of the drivermay include analyzing the sensor data to identify at least one of theone or more driving behaviors.

Additionally or alternatively, analyzing the received telematics data toidentify the at least one driving behavior may include analyzing thereceived telematics data to identify one or both of: a plurality ofdistances, during the one or more time periods, between the vehicle andother vehicles; and lane usage of the vehicle during the one or moretime periods.

Additionally or alternatively, receiving telematics data may includereceiving operational data indicative of how the driver operated thevehicle during the one or more time periods; and analyzing the receivedtelematics data to identify one or more driving behaviors of the drivermay include analyzing the operational data to identify at least one ofthe one or more driving behaviors.

Additionally or alternatively, analyzing the received telematics data toidentify the one or more time periods during which the driver drove withone or more passengers may include determining a specific number ofpassengers during each of the one or more time periods, and setting atleast the portion of the driver profile based at least upon thedetermined one or more driving behaviors of the driver during the one ormore time periods may include setting at least the portion of the driverprofile based further on the specific number of passengers during eachof the one or more time periods.

Additionally or alternatively, causing transmission of at least theportion of the driver profile to an entity may include causingtransmission of at least the portion of the driver profile to afinancial institution that adjusts the credit rating associated with thedriver based upon at least the portion of the driver profile.

Additionally or alternatively, causing transmission of at least theportion of the driver profile to an entity may include causingtransmission of at least the portion of the driver profile to anemployer that reviews at least the portion of the driver profile inconnection with the job sought by the driver.

Additionally or alternatively, causing transmission of at least theportion of the driver profile to an entity may include causingtransmission of at least the portion of the driver profile to an insurerthat adjusts the insurance rating of the driver based upon at least theportion of the driver profile.

Additionally or alternatively, causing transmission of at least theportion of the driver profile to an entity may include causingtransmission of at least the portion of the driver profile to a rentalvehicle company that discounts a car rental offered to the driver basedupon at least the portion of the driver profile.

In another aspect, a computer-implemented method may include: (1)receiving telematics data that was collected during one or more timeperiods by one or more electronic subsystems located on or in a vehicle,and/or by a mobile electronic device or one or more mobile electronicdevice sensors, wherein receiving the telematics data may includereceiving operational data indicative of how a driver of the vehicleoperated the vehicle during the one or more time periods; (2) analyzing,by one or more processors, the received telematics data to identify oneor more driving behaviors of the driver during the one or more timeperiods; (3) generating or modifying, by the one or more processors andbased at least upon the one or more driving behaviors of the driver, adriver profile associated with the driver; (4) identifying, by one ormore processors and based at least upon the generated or modified driverprofile, a suggested vehicle type, wherein identifying the suggestedvehicle type may include determining that the generated or modifieddriver profile meets a set of one or more matching criteria associatedwith the suggested vehicle type; and/or (5) causing, by the one or moreprocessors, an indication of the suggested vehicle type to be displayedto a user. The method may include additional, fewer, and/or alternateactions, including those discussed elsewhere herein.

For instance, in various aspects, analyzing the received telematics datato identify the one or more driving behaviors of the driver during theone or more time periods may include identifying one or more of (i)acceleration patterns of the driver, (ii) braking patterns of thedriver, or (iii) cornering patterns of the driver, and generating ormodifying the driver profile based at least upon the one or more drivingbehaviors may include causing the driver profile to indicate one or moreof (i) an acceleration preference of the driver, (ii) a brakingpreference of the driver, or (iii) a cornering preference of the driver.

Additionally or alternatively, determining that the generated ormodified driver profile meets the set of one or more matching criteriamay include determining one or more of (i) that the accelerationpreference of the driver meets a first criterion of the set of matchingcriteria, (ii) that the braking preference of the driver meets a secondcriterion of the set of matching criteria, or (iii) that the corneringpreference of the driver meets a third criterion of the set of matchingcriteria.

Additionally or alternatively, receiving the telematics data further mayinclude receiving data indicative of how often the driver used one ormore features of the vehicle during the one or more time periods, theone or more features not including features for controlling any ofacceleration, braking or steering of the vehicle.

Additionally or alternatively, generating or modifying the driverprofile associated with the driver may include causing the driverprofile to indicate one or more preferred features, and determining thatthe generated or modified driver profile meets a set of one or morematching criteria associated with the suggested vehicle type may includedetermining that the suggested vehicle type provides the one or morepreferred features.

Additionally or alternatively, receiving the telematics data further mayinclude receiving sensor data indicative of an environment external tothe vehicle during the one or more time periods, analyzing the receivedtelematics data may include analyzing the sensor data to identify aplurality of distances, during the one or more time periods, between thevehicle and other vehicles, and generating or modifying the driverprofile may be further based upon the plurality of distances.

Additionally or alternatively, receiving the telematics data may furtherinclude receiving sensor data indicative of an environment external tothe vehicle during the one or more time periods, analyzing the receivedtelematics data may include analyzing the sensor data to identifyweather conditions during the one or more time periods, and generatingor modifying the driver profile may further be based upon the weatherconditions.

Additionally or alternatively, identifying the suggested vehicle typemay include identifying a specific vehicle make. Additionally oralternatively, identifying the suggested vehicle type may includeidentifying a specific vehicle model. Additionally or alternatively,identifying the suggested vehicle type may include causing the generatedor modified driver profile to be transmitted to a third party, andreceiving the indication of the suggested vehicle type from the thirdparty.

Additionally or alternatively, causing the indication of the suggestedvehicle type to be displayed to the user may include transmitting, via acomputer network, the indication of the suggested vehicle type to acomputing device of the user.

In another aspect, a computer-implemented method may include: (1)receiving telematics data that was collected during one or more timeperiods by one or more electronic subsystems located on or in a vehicle,and/or by a mobile electronic device or one or more mobile electronicdevice sensors, wherein receiving the telematics data may includereceiving operational data indicative of how a driver of the vehicleoperated the vehicle during the one or more time periods; (2) analyzing,by one or more processors, the received telematics data to identify oneor more driving behaviors of the driver during the one or more timeperiods; (3) generating or modifying, by the one or more processors andbased at least upon the one or more of driving behaviors, a driverprofile associated with the driver; (4) identifying, by the one or moreprocessors, a suggested vehicle component type matching the generated ormodified driver profile, wherein identifying the suggested vehiclecomponent type may include determining that the generated or modifieddriver profile meets a set of one or more matching criteria associatedwith the suggested vehicle component type; and/or (5) causing, by theone or more processors, an indication of the suggested vehicle componenttype to be displayed to a user. The method may include additional,fewer, and/or alternate actions, including those discussed elsewhereherein.

For instance, in various aspects, analyzing the received telematics datato identify the one or more driving behaviors of the driver during theone or more time periods may include identifying one or more of (i)acceleration patterns of the driver, (ii) braking patterns of thedriver, or (iii) cornering patterns of the driver, and generating ormodifying the driver profile based at least upon the one or more drivingbehaviors may include causing the driver profile to indicate one or moreof (i) an acceleration preference of the driver, (ii) a brakingpreference of the driver, or (iii) a cornering preference of the driver.

Additionally or alternatively, determining that the generated ormodified driver profile meets the set of one or more matching criteriamay include determining one or more of (i) that the accelerationpreference of the driver meets a first criterion of the set of matchingcriteria, (ii) that the braking preference of the driver meets a secondcriterion of the set of matching criteria, or (iii) that the corneringpreference of the driver meets a third criterion of the set of matchingcriteria.

Additionally or alternatively, receiving the telematics data may furtherinclude receiving sensor data indicative of an environment external tothe vehicle during the one or more time periods, analyzing the receivedtelematics data may include analyzing the sensor data to identify aplurality of distances, during the one or more time periods, between thevehicle and other vehicles, and generating or modifying the driverprofile may further be based upon the plurality of distances.

Additionally or alternatively, receiving the telematics data further mayinclude receiving sensor data indicative of an environment external tothe vehicle during the one or more time periods, analyzing the receivedtelematics data may include analyzing the sensor data to identifyweather conditions during the one or more time periods, and generatingor modifying the driver profile may further be based upon the weatherconditions.

Additionally or alternatively, identifying the suggested vehiclecomponent type may include identifying a specific part number.Additionally or alternatively, identifying the suggested vehiclecomponent type may include causing the generated or modified driverprofile to be transmitted to a third party, and receiving the indicationof the suggested vehicle component type from the third party.Additionally or alternatively, causing the indication of the suggestedvehicle component type to be displayed to the user may includetransmitting, via a computer network, the indication of the suggestedvehicle component type to a computing device of the user.

Xv. Exemplary System Embodiments

In one aspect, a computer system for detecting and acting upon driverresponsiveness to vehicle alerts may include: (1) one or moreprocessors; and (2) a memory storing instructions that, when executed bythe one or more processors, cause the computer system to (a) determinethat an on-board system of a vehicle indicated, to a driver of thevehicle and at a first time, that a subsystem of the vehicle requiresrepair, service or maintenance, (b) detect an amount of time elapsedsince the first time without the subsystem being repaired, serviced ormaintained, (c) set, based at least upon the detected amount of timeelapsed since the first time, a at least a portion of a driver profileassociated with the driver, and/or (d) transmit at least the portion ofthe driver profile to an entity that (i) adjusts a credit ratingassociated with the driver based upon at least the portion of the driverprofile, (ii) adjusts an insurance rating associated with the driverbased upon at least the portion of the driver profile, (iii) reviews atleast the portion of the driver profile in connection with a job soughtby the driver, and/or (iv) offers a permanent or temporary credit, inconnection with a good or service offered by the entity, based upon atleast the portion of the driver profile. The system may includeadditional, less, or alternate functionality, including that discussedelsewhere herein.

For instance, in various aspects, the instructions may cause thecomputer system to determine that the on-board system of the vehicleindicated that the subsystem of the vehicle requires repair, service ormaintenance at least by receiving vehicle data generated by the on-boardsystem of the vehicle, the vehicle data including one or more diagnosticfault codes.

Additionally or alternatively, the vehicle data may further include aplurality of time stamps associated with the one or more diagnosticfault codes, and the instructions may cause the computer system todetect the amount of time elapsed since the first time at least bycalculating a time difference between two time stamps of the pluralityof time stamps.

In another aspect, a computer system for detecting and acting upondriver compliance with driver-specific limitations may include: (1) oneor more processors; and (2) a memory storing instructions that, whenexecuted by the one or more processors, cause the computer system to (a)determine that a driver of a vehicle has one or more limitationsspecific to one or both of (i) a medical condition of the driver, and(ii) a physical characteristic of the driver, (b) receive telematicsdata that was collected during one or more time periods by one or bothof (i) one or more electronic subsystems located on or in the vehicleand (ii) a mobile electronic device of the driver or a passenger, (c)analyze the received telematics data to identify a plurality of drivingbehaviors of the driver during the one or more time periods, (d)determine, based at least upon the plurality of driving behaviors, alevel of compliance with the one or more limitations during the one ormore time periods, (e) based at least upon the determined level ofcompliance, set a at least a portion of a driver profile associated withthe driver, and/or (f) transmit at least the portion of the driverprofile to an entity that (i) adjusts a credit rating associated withthe driver based at least upon at least the portion of the driverprofile, (ii) adjusts an insurance rating associated with the driverbased upon at least the portion of the driver profile, (iii) reviews atleast the portion of the driver profile in connection with a job soughtby the driver, and/or (iv) offers a permanent or temporary credit, inconnection with a good or service offered by the entity, based upon atleast the portion of the driver profile. The system may includeadditional, less, or alternate functionality, including that discussedelsewhere herein.

For instance, in various aspects, the one or more limitations mayinclude one or both of (i) impaired vision and (ii) impaired motorskills. Additionally or alternatively, the telematics data may includesensor data indicative of an environment external to the vehicle duringthe one or more time periods. Additionally or alternatively, thetelematics data may include operational data indicative of a pluralityof speeds of the vehicle during the one or more time periods.

In another aspect, a computer system for detecting and acting upondriver behavior while driving with passengers may include: (1) one ormore processors; and (2) a memory storing instructions that, whenexecuted by the one or more processors, cause the computer system to (a)receive telematics data that was collected by one or both of (i) one ormore electronic subsystems located on or in a vehicle and (ii) a mobileelectronic device of a driver or a passenger in the vehicle, or by oneor more mobile device sensors or applications, (b) analyze the receivedtelematics data to (i) identify one or more time periods during whichthe driver of the vehicle drove with one or more passengers, and (ii)identify one or more driving behaviors of the driver during the one ormore time periods, (c) based at least upon the determined one or moredriving behaviors of the driver during the one or more time periods, setat least a portion of a driver profile associated with the driver,and/or (d) transmit at least the portion of the driver profile to anentity that (i) adjusts a credit rating associated with the driver basedupon at least the portion of the driver profile, (ii) adjusts aninsurance rating associated with the driver based upon at least theportion of the driver profile, (iii) reviews at least the portion of thedriver profile in connection with a job sought by the driver, and/or(iv) offers a permanent or temporary credit, in connection with a goodor service offered by the entity, based upon at least the portion of thedriver profile. The system may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

For instance, in various aspects, the telematics data may include imagedata that was collected by a camera mounted within the vehicle, and theinstructions may cause the computer system to analyze the receivedtelematics data at least by applying an image recognition algorithm tothe image data to determine when passengers were within the vehicle.

Additionally or alternatively, the telematics data may include weightsensor data that was collected by one or more weight sensors installedwithin one or more seats of the vehicle, and the instructions may causethe computer system to analyze the received telematics data at least byanalyzing the weight sensor data to determine when passengers werewithin the vehicle.

Additionally or alternatively, the telematics data may include seat beltdata that was collected by one or more sensors installed within thevehicle, and the instructions may cause the computer system to analyzethe received telematics data at least by analyzing the seat belt data todetermine when passengers were within the vehicle.

Additionally or alternatively, the instructions may cause the computersystem to analyze the received telematics data at least by analyzing thereceived telematics data to identify one or both of: (i) a plurality ofdistances, during the one or more time periods, between the vehicle andother vehicles; and (ii) lane usage of the vehicle during the one ormore time periods.

In another aspect, a computer system may include: (1) one or moreprocessors; and (2) a memory storing instructions that, when executed bythe one or more processors, cause the computer system to (a) receivetelematics data that was collected during one or more time periods byone or more electronic subsystems located on or in a vehicle, and/or bya mobile electronic device, the telematics data including operationaldata indicative of how a driver of the vehicle operated the vehicleduring the one or more time periods, (b) analyze the received telematicsdata to identify one or more driving behaviors of the driver during theone or more time periods, (c) generate or modify, based at least uponthe one or more driving behaviors of the driver, a driver profileassociated with the driver, (d) identify, based at least upon thegenerated or modified driver profile, a suggested vehicle type, at leastby determining that the generated or modified driver profile meets a setof one or more matching criteria associated with the suggested vehicletype, and/or (e) cause an indication of the suggested vehicle type to bedisplayed to a user. The system may include additional, less, oralternate functionality, including that discussed elsewhere herein.

For instance, in various aspects, the one or more driving behaviors ofthe driver during the one or more time periods may include one or moreof (i) acceleration patterns of the driver, (ii) braking patterns of thedriver, or (iii) cornering patterns of the driver, and the instructionsmay cause the computer system to generate or modify the driver profilebased at least upon the one or more driving behaviors at least bycausing the driver profile to indicate one or more of (i) anacceleration preference of the driver, (ii) a braking preference of thedriver, or (iii) a cornering preference of the driver.

Additionally or alternatively, the telematics data may further includedata indicative of how often the driver used one or more features of thevehicle during the one or more time periods, and wherein the one or morefeatures do not include features for controlling any of acceleration,braking or steering of the vehicle.

Additionally or alternatively, the instructions may cause the computersystem to (1) generate or modify the driver profile associated with thedriver at least by causing the driver profile to indicate one or morepreferred features, and (2) determine that the generated or modifieddriver profile meets the set of one or more matching criteria associatedwith the suggested vehicle type at least by determining that thesuggested vehicle type provides the one or more preferred features.

Additionally or alternatively, the telematics data may further includesensor data indicative of an environment external to the vehicle duringthe one or more time periods, the instructions may cause the computingsystem to analyze the received telematics data at least by analyzing thesensor data to identify a plurality of distances, during the one or moretime periods, between the vehicle and other vehicles, and theinstructions may cause the computing system to generate or modify thedriver profile further based upon the plurality of distances.

Additionally or alternatively, the telematics data may further includesensor data indicative of an environment external to the vehicle duringthe one or more time periods, the instructions may cause the computingsystem to analyze the received telematics data at least by analyzing thesensor data to identify weather conditions during the one or more timeperiods, and the instructions may cause the computing system to generateor modify the driver profile further based upon the weather conditions.

In another aspect, a computer system may include: (1) one or moreprocessors; and (2) a memory storing instructions that, when executed bythe one or more processors, cause the computer system to (a) receivetelematics data that was collected during one or more time periods byone or more electronic subsystems located on or in a vehicle, and/or bya mobile electronic device or one or more mobile electronic devicesensors, wherein receiving the telematics data may include receivingoperational data indicative of how a driver of the vehicle operated thevehicle during the one or more time periods, (b) analyze the receivedtelematics data to identify one or more driving behaviors of the driverduring the one or more time periods, (c) generate or modify, based atleast upon the one or more driving behaviors, a driver profileassociated with the driver, (d) identify a suggested vehicle componenttype matching the generated or modified driver profile, whereinidentifying the suggested vehicle component type may include determiningthat the generated or modified driver profile meets a set of one or morematching criteria associated with the suggested vehicle component type,and/or (e) cause an indication of the suggested vehicle component typeto be displayed to a user. The system may include additional, less, oralternate functionality, including that discussed elsewhere herein.

For instance, in various aspects, the one or more driving behaviors ofthe driver during the one or more time periods may include one or moreof (i) acceleration patterns of the driver, (ii) braking patterns of thedriver, or (iii) cornering patterns of the driver, and the instructionsmay cause the computer system to generate or modify the driver profilebased at least upon the one or more driving behaviors at least bycausing the driver profile to indicate one or more of (i) anacceleration preference of the driver, (ii) a braking preference of thedriver, or (iii) a cornering preference of the driver.

Additionally or alternatively, the instructions may cause the computersystem to determine that the generated or modified driver profile meetsthe set of one or more matching criteria at least by determining one ormore of (i) that the acceleration preference of the driver meets a firstcriterion of the set of matching criteria, (ii) that the brakingpreference of the driver meets a second criterion of the set of matchingcriteria, or (iii) that the cornering preference of the driver meets athird criterion of the set of matching criteria.

Additionally or alternatively, the telematics data may further includesensor data indicative of an environment external to the vehicle duringthe one or more time periods, the instructions may cause the computingsystem to analyze the received telematics data at least by analyzing thesensor data to identify a plurality of distances, during the one or moretime periods, between the vehicle and other vehicles, and theinstructions may cause the computing system to generate or modify thedriver profile further based upon the plurality of distances.

Additionally or alternatively, the telematics data may further includesensor data indicative of an environment external to the vehicle duringthe one or more time periods, the instructions may cause the computingsystem to analyze the received telematics data at least by analyzing thesensor data to identify weather conditions during the one or more timeperiods, and the instructions may cause the computing system to generateor modify the driver profile further based upon the weather conditions.

Additionally or alternatively, the suggested vehicle component type maybe a specific part number. Additionally or alternatively, theinstructions may cause the computer system to identify the suggestedvehicle component type at least by: (1) causing the generated ormodified driver profile to be transmitted to a third party; and (2)receiving the indication of the suggested vehicle component type fromthe third party.

Xvi. Additional Considerations

With the foregoing, an insurance customer may opt-in to a rewards,insurance discount, or other type of program. After the insurancecustomer provides their affirmative consent, an insurance providerremote server may collect data from the customer’s mobile device, smarthome controller, or other smart devices - such as with the customer’spermission or affirmative consent. The data collected may be related tosmart home functionality (or home occupant preferences or preferenceprofiles), and/or insured assets before (and/or after) aninsurance-related event, including those events discussed elsewhereherein. In return, risk averse insureds, home owners, or home orapartment occupants may receive discounts or insurance cost savingsrelated to home, renters, personal articles, auto, and other types ofinsurance from the insurance provider.

In one aspect, smart or interconnected home data, and/or other data,including the types of data discussed elsewhere herein, may be collectedor received by an insurance provider remote server, such as via director indirect wireless communication or data transmission from a smarthome controller, mobile device, or other customer computing device,after a customer affirmatively consents or otherwise opts-in to aninsurance discount, reward, or other program. The insurance provider maythen analyze the data received with the customer’s permission to providebenefits to the customer. As a result, risk averse customers may receiveinsurance discounts or other insurance cost savings based upon data thatreflects low risk behavior and/or technology that mitigates or preventsrisk to (i) insured assets, such as homes, personal belongings, orvehicles, and/or (ii) home or apartment occupants.

The patent claims at the end of this patent application are not intendedto be construed under 35 U.S.C. § 112(f) unless traditionalmeans-plus-function language is expressly recited, such as “means for”or “step for” language being explicitly recited in the claim(s). Thesystems and methods described herein are directed to an improvement tocomputer functionality, and improve the functioning of conventionalcomputers.

The following considerations also apply to the foregoing discussion.Throughout this specification, plural instances may implement operationsor structures described as a single instance. Although individualoperations of one or more methods are illustrated and described asseparate operations, one or more of the individual operations may beperformed concurrently, and nothing requires that the operations beperformed in the order illustrated. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Unless specifically stated otherwise, discussions herein using wordssuch as “processing,” “computing,” “calculating,” “determining,”“presenting,” “displaying,” or the like may refer to actions orprocesses of a machine (e.g., a computer) that manipulates or transformsdata represented as physical (e.g., electronic, magnetic, or optical)quantities within one or more memories (e.g., volatile memory,non-volatile memory, or a combination thereof), registers, or othermachine components that receive, store, transmit, or displayinformation.

As used herein any reference to “one embodiment” or “an embodiment”means that a particular element, feature, structure, or characteristicdescribed in connection with the embodiment is included in at least oneembodiment. The appearances of the phrase “in one embodiment” in variousplaces in the specification are not necessarily all referring to thesame embodiment.

As used herein, the terms “comprises,” “comprising,” “includes,”“including,” “has,” “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily limited to only those elements but may include otherelements not expressly listed or inherent to such process, method,article, or apparatus. Further, unless expressly stated to the contrary,“or” refers to an inclusive or and not to an exclusive or. For example,a condition A or B is satisfied by any one of the following: A is true(or present) and B is false (or not present), A is false (or notpresent) and B is true (or present), and both A and B are true (orpresent).

In addition, use of “a” or “an” is employed to describe elements andcomponents of the embodiments herein. This is done merely forconvenience and to give a general sense of the invention. Thisdescription should be read to include one or at least one and thesingular also includes the plural unless it is obvious that it is meantotherwise.

Upon reading this disclosure, those of skill in the art will appreciatestill additional alternative structural and functional designs forgenerating, modifying, and/or using driver profiles through theprinciples disclosed herein. Thus, while particular embodiments andapplications have been illustrated and described, it is to be understoodthat the disclosed embodiments are not limited to the preciseconstruction and components disclosed herein. Various modifications,changes and variations, which will be apparent to those skilled in theart, may be made in the arrangement, operation and details of the methodand apparatus disclosed herein without departing from the spirit andscope defined in the appended claims.

We claim:
 1. A computer-implemented method for detecting and acting upondriver behavior while driving with passengers, the computer-implementedmethod comprising: collecting telematics data by one or both of (i) oneor more electronic subsystems located on or in a vehicle and (ii) amobile electronic device of a driver or a passenger in the vehicle,wherein collecting the telematics data includes collecting exteriorsensor data by one or more sensors indicative of an environment externalto the vehicle; transmitting, by the one or more electronic subsystemsor by the mobile electronic device, the telematics data to a computersystem; identifying, by analyzing the collected telematics data with oneor more processors of the computer system, (i) one or more time periodsduring which the driver drove with one or more passengers, (ii) one ormore other time periods during which the driver drove withoutpassengers, (iii) one or more driving behaviors of the driver during theone or more time periods, and (iv) one or more driving behaviors of thedriver during the one or more other time periods; determining, by one ormore processors of the computer system and based upon (i) the one ormore driving behaviors of the driver during the one or more time periodsand (ii) the one or more driving behaviors of the driver during the oneor more other time periods, how the driver modifies his or her drivingwhen driving with passengers as compared to when driving alone; andconveying to an entity, by the one or more processors of the computersystem via a network, at least a portion of a driver profile associatedwith the driver that has been adjusted based upon how the drivermodifies his or her driving.
 2. The computer-implemented method of claim1, wherein the one or more driving behaviors of the driver include oneor both of (a) distance between the vehicle and other vehicles, and (b)lane usage of the vehicle.
 3. The computer-implemented method of claim2, wherein analyzing the collected telematics data includes analyzingthe collected external sensor data to identify a plurality of distancesbetween the vehicle and other vehicles.
 4. The computer-implementedmethod of claim 1, wherein the one or more driving behaviors of thedriver include (a) distance between the vehicle and the other vehicles,and (b) lane usage of the vehicle.
 5. The computer-implemented method ofclaim 1, the method further comprising, based at least upon how thedriver modifies his or her driving when driving with passengers,setting, by the one or more processors, at least the portion of thedriver profile associated with the driver.
 6. The computer-implementedmethod of claim 1, wherein collecting the telematics data includescollecting operational data indicative of how the driver operated thevehicle during the one or more time periods and how the driver operatedthe vehicle during the one or more other time periods.
 7. Thecomputer-implemented method of claim 6, comprising: identifying at leastone of the one or more driving behaviors by analyzing the operationaldata.
 8. The computer-implemented method of claim 1, wherein the entityis an entity that, based upon at least the portion of the driverprofile, adjusts a credit rating associated with the driver.
 9. Thecomputer-implemented method of claim 1, wherein the entity is an entitythat reviews at least the portion of the driver profile in connectionwith a job sought by the driver.
 10. The computer-implemented method ofclaim 1, wherein the entity is an entity that, based upon at least theportion of the driver profile, offers a permanent or temporary credit inconnection with a good or service offered by the entity.
 11. A systemfor detecting and acting upon driver behavior while driving withpassengers, the system comprising: a device or subsystem that includesone or both of (i) one or more electronic subsystems located on or in avehicle, and (ii) a mobile electronic device of a driver or a passengerof the vehicle, and is configured to collect telematics data, includingexternal sensor data that is generated by one or more sensors andindicative of an environment external to the vehicle, and transmit thetelematics data to a computer system; and the computer system, thecomputer system comprising one or more processors and a memory, whereinthe memory stores instructions that, when executed by the one or moreprocessors, cause the computer system to identify, by analyzing thecollected telematics data, (i) one or more time periods during which thedriver of the vehicle drove with one or more passengers, (ii) one ormore other time periods during which the driver drove withoutpassengers, (iii) one or more driving behaviors of the driver during theone or more time periods, and (iv) one or more driving behaviors of thedriver during the one or more other time periods, determine, based upon(i) the one or more driving behaviors of the driver during the one ormore time periods and (ii) the one or more driving behaviors of thedriver during the one or more other time periods, how the drivermodifies his or her driving when driving with passengers as compared towhen driving alone, and convey to an entity, via a network, at least aportion of a driver profile associated with the driver that has beenadjusted based upon how the driver modifies his or her driving.
 12. Thesystem of claim 11, wherein the one or more driving behaviors of thedriver include one or both of (a) distance between the vehicle and othervehicles, and (b) lane usage of the vehicle.
 13. The system of claim 12,wherein analyzing the collected telematics data includes analyzing thecollected external sensor data to identify a plurality of distancesbetween the vehicle and other vehicles.
 14. The system of claim 11,wherein the one or more driving behaviors of the driver include (a)distance between the vehicle and the other vehicles, and (b) lane usageof the vehicle.
 15. The system of claim 11, wherein the instructionfurther cause the computer system to, based at least upon how the drivermodifies his or her driving when driving with passengers, set at leastthe portion of the driver profile associated with the driver.
 16. Thesystem of claim 11, wherein collecting the telematics data includescollecting operational data indicative of how the driver operated thevehicle during the one or more time periods and how the driver operatedthe vehicle during the one or more other time periods.
 17. The system ofclaim 16, wherein the instructions cause the computer system to identifyat least one of the one or more driving behaviors by analyzing theoperational data.
 18. The system of claim 11, wherein the entity is anentity that, based upon at least the portion of the driver profile,adjusts a credit rating associated with the driver.
 19. The system ofclaim 11, wherein the entity is an entity that reviews at least theportion of the driver profile in connection with a job sought by thedriver.
 20. The system of claim 11, wherein the entity is an entitythat, based upon at least the portion of the driver profile, offers apermanent or temporary credit in connection with a good or serviceoffered by the entity.